Mlflow Jobs in Bengaluru

Data Scientist I Job Type: Full-Time Category: Data Science Location: Bangalore About Bright Money Bright is a mission-driven consumer fintech company helping Americans get out of debt and build stronger financial futures powered by data science and machine learning. Our mobile platform provides personalized tools for credit building, debt paydown, budgeting, and loan refinancing. With 300,000+ users, 100,000+ reviews, and support from top-tier investors like Sequoia, Falcon Edge, and Hummingbird, Bright is one of the fastest-growing fintech startups in the U.S. We ve raised $90M+ in equity and debt funding to date. We're proud to be building a global-first, data-driven consumer tech company from India, for the world. About the Role As a Data Scientist I, you will be part of a high-impact team using data and machine learning to power Bright s core financial products. You ll work on problems that directly improve users financial outcomes modeling behavior, predicting intent, and enabling smarter, automated experiences. This is a hands-on role for someone with strong fundamentals in ML, statistics, and programming, and a desire to turn data into real-world product impact. Key Responsibilities Design and build predictive models using core concepts of machine learning, statistics, and probability. Analyze large-scale user and transactional data to extract insights and inform strategy. Collaborate cross-functionally with product managers, engineers, and business stakeholders to define and solve problems. Deploy ML models into production environments, ensuring scalability, stability, and performance. Tune, evaluate, and interpret model results to maximize business value and user outcomes. Document methodologies and workflows for reproducibility and team collaboration. Stay current with AI/ML advancements and experiment with new techniques as appropriate. Required Qualifications Bachelor s or Master s degree in Computer Science, Statistics, Mathematics, or a related quantitative field. Strong grasp of ML and statistical concepts (e.g., regression, classification, hypothesis testing, probability distributions). Proficiency in Python or R, and experience with ML libraries such as scikit-learn, TensorFlow, or PyTorch. Familiarity with model deployment tools and frameworks (e.g., Docker, Flask/FastAPI, MLflow). Understanding of how to implement and monitor models in a real-world production environment. Awareness of modern AI techniques including transformers, LLMs, and generative AI. Strong problem-solving skills, curiosity, and ability to communicate complex ideas clearly. Exposure to cloud platforms like AWS, GCP, or Azure is a plus. Bonus Points For Experience with deep learning and advanced neural network architectures. Understanding of MLOps best practices (CI/CD for ML, monitoring, retraining pipelines). Personal projects, open-source contributions, or research publications in AI/ML. What You ll Work On Model user behavior and financial patterns to power intelligent product features. Analyze complex transaction datasets to surface actionable insights. Build and deploy ML systems that personalize savings and debt management strategies. Apply deep learning, reinforcement learning, and LLMs to real-world fintech use cases. Collaborate with engineering and product teams to launch data-powered experiences in the Bright app. Experiment with cutting-edge AI technologies to innovate in consumer finance. At Bright, you ll go beyond theory you ll use data to change lives. This is your chance to build meaningful, scalable machine learning systems that empower users to take control of their financial future. Qualification : Bachelors or Masters degree in Computer Science, Statistics, Mathematics, or a related quantitative field

Job Title: Associate ML Ops Location: Bangalore Department: Data Science Employment Type: Full-time Experience: 1 2 years Job Overview We are seeking a motivated and detail-oriented Associate ML Ops to join our Data Science team. In this role, you will be responsible for supporting the deployment, monitoring, and scaling of machine learning models in production environments. You ll collaborate closely with data scientists and engineers to build robust MLOps pipelines and ensure model reliability, scalability, and performance. If you are passionate about bringing machine learning models to life and have hands-on experience in productionizing ML systems, we d love to hear from you. Key Responsibilities Deploy and maintain machine learning models in production environments using best-in-class tools like Databricks and MLflow. Collaborate with data scientists to translate experimental models into scalable, production-ready systems. Monitor model performance, accuracy, and overall health through automated tools and custom strategies. Build and maintain RESTful APIs using Python frameworks such as Flask or Django to serve ML models. Write efficient and optimized SQL and NoSQL queries for data extraction and transformation. Apply software engineering best practices, including version control, testing, and documentation, to MLOps workflows. Work with Python libraries like Pandas, PySpark, scikit-learn, SQLAlchemy, and Requests. Troubleshoot issues related to model deployment, API performance, or data integration pipelines. Minimum Qualifications Bachelor s or Master s degree in Computer Science, Statistics, Econometrics, Operations Research, or a related technical field. 1 2 years of hands-on experience in solving analytical or machine learning problems in production settings. Must-Have Technical Skills Hands-on experience with Databricks and MLflow Proven expertise in deploying ML models in real-world applications Strong understanding of data structures, algorithms, OOP, and software engineering principles Experience building and maintaining REST APIs using Python Proficiency in SQL and NoSQL Excellent Python programming and debugging skills Familiarity with core Python libraries used in ML and data processing: Pandas, scikit-learn, PySpark, SQLAlchemy, etc. Nice-to-Have Skills Exposure to Kafka for streaming and batch data processing Familiarity with Git and CI/CD pipelines Experience with Python multiprocessing or worker/queue systems Understanding of event-driven or asynchronous programming models This is an exciting opportunity to work at the intersection of data science and engineering. You ll play a key role in productionizing cutting-edge models and ensuring they deliver real business impact. Qualification : Bachelors or Masters degree in Computer Science, Statistics, Econometrics, Operations Research, or a related technical field

Job Title: ML Ops Engineer Location: Bangalore Department: Data Science Employee Type: Full-time Experience Required: 3 5 years Position Overview We are seeking an experienced and motivated ML Ops Engineer to join our Data Science team. In this role, you will be responsible for deploying, monitoring, and maintaining machine learning models in production environments. You will work closely with data scientists, engineers, and product teams to ensure models are scalable, reliable, and aligned with business objectives. This role is ideal for professionals who are passionate about building robust ML pipelines and bringing machine learning solutions into real-world applications at scale. Key Responsibilities Deploy and manage machine learning models in production environments, ensuring scalability, reliability, and performance. Build and maintain MLOps pipelines using platforms like Databricks and MLflow. Monitor model performance, accuracy, and health; implement alerting and diagnostics as needed. Develop and maintain RESTful APIs using Python frameworks such as Flask or Django to serve ML models. Optimize data workflows and collaborate with engineering teams to improve model integration and performance. Design strategies for automated model retraining, deployment, and version control. Write clean, maintainable, and efficient code using Python, adhering to OOP principles and best practices. Write complex queries using SQL and work with NoSQL databases to support data pipelines and feature stores. Leverage Python libraries such as PySpark, Pandas, scikit-learn, SQLAlchemy, and Requests. Minimum Qualifications Bachelor s or Master s degree in Computer Science, Statistics, Econometrics, Operations Research, or a related technical field. 3 5 years of experience in building, deploying, and monitoring machine learning solutions in production. Must-Have Skills Experience with Databricks and MLflow for model training and deployment. Proven expertise in machine learning model deployment and monitoring in live environments. Strong programming skills in Python, with solid understanding of data structures, algorithms, and OOP concepts. Experience developing RESTful APIs using Flask or Django. Proficient in SQL and NoSQL database operations. Hands-on knowledge of libraries such as Pandas, PySpark, scikit-learn, SQLAlchemy, and Requests. Strong analytical, problem-solving, and debugging skills. Good-to-Have Skills Experience with Kafka streaming and batch processing. Familiarity with CI/CD pipelines and version control systems like Git. Understanding of Python multiprocessing, worker/queue systems, and asynchronous/event-driven programming. This is a unique opportunity to work at the intersection of machine learning and DevOps. You'll play a critical role in operationalizing AI models and making them a core part of our product offerings. If you enjoy building scalable systems and solving real-world ML engineering challenges, we d love to meet you. Qualification : Bachelors or Masters degree in Computer Science, Statistics, Econometrics, Operations Research, or a related technical field

Position Title: Lead AI/ML Engineer Location: Bengaluru Bellandur (GTP) Employment Type: Full-time Job Summary Synechron is seeking a seasoned Lead AI/ML Engineer to lead cutting-edge initiatives in artificial intelligence and machine learning. This role requires deep technical expertise in AI/ML, including deep learning, NLP, computer vision, and generative AI, combined with strong leadership skills to manage teams and drive innovation. You will collaborate closely with stakeholders to deliver high-impact solutions and play a key role in shaping the company s AI-driven digital transformation. Key Responsibilities Lead end-to-end development of AI/ML solutions across use cases involving machine learning, deep learning, computer vision, NLP, and generative AI. Design and implement scalable models and algorithms, ensuring performance, accuracy, and interpretability. Collaborate with product owners, engineers, and business stakeholders to align AI/ML initiatives with strategic objectives. Mentor and guide data scientists and ML engineers to elevate technical quality and delivery standards. Continuously evaluate emerging AI technologies, frameworks, and methodologies to enhance team capabilities. Contribute to innovation strategy by identifying new business opportunities driven by AI/ML. Ensure data and model governance, ethical AI practices, and responsible deployment of AI solutions. Required Skills & Tools Core Competencies: Strong hands-on experience in machine learning, deep learning, NLP, computer vision, and generative AI. Expertise in Python (primary), with additional knowledge of R, SQL, Java, or C++. Deep understanding of statistics, linear algebra, probability, and algorithm design. Frameworks & Tools: TensorFlow, PyTorch, Keras, OpenCV, Hugging Face, spaCy, Scikit-learn, etc. Data processing tools like Pandas, NumPy, and Spark. Version control and CI/CD tools (e.g., Git, MLflow, Docker, Airflow). Methodologies: Proficient in Agile development and model lifecycle management. Experience with productionizing AI models and deploying them on cloud platforms (AWS, Azure, GCP). Experience 8 12 years of experience in AI/ML, Data Science, or related domains. Minimum 8+ years in a leadership or technical lead role driving successful AI/ML initiatives. Proven record of delivering high-impact AI/ML projects at scale. Experience mentoring and managing AI/ML teams in collaborative, cross-functional environments. Day-to-Day Activities Direct and oversee AI/ML model development, validation, deployment, and monitoring. Review project designs, provide technical oversight, and conduct code/model reviews. Drive research and experimentation to apply novel AI methods to solve real-world problems. Support proposal development and client engagements with AI/ML subject matter expertise. Foster a culture of continuous learning, innovation, and data-driven thinking. Qualifications Bachelor s or Master s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Relevant certifications (e.g., TensorFlow, AWS Machine Learning, Azure AI Engineer) are a plus. Soft Skills Strong leadership, team management, and mentoring capabilities. Excellent communication and stakeholder engagement skills. Strategic thinking with a passion for innovation and emerging technologies. Ability to thrive in a dynamic, fast-paced environment and lead through ambiguity. Diversity & Inclusion at Synechron Synechron is committed to a diverse and inclusive workplace. Through our Same Difference DEI initiative, we celebrate unique backgrounds and perspectives while fostering a respectful, empowering environment. We welcome applications from candidates of all identities and provide support through mentoring, internal mobility, and flexible work arrangements. Qualification : Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Distinguished Engineer Machine Learning Engineering Location: Bangalore Company: Capital One India About Us At Capital One India, we re redefining how technology powers financial services. Our teams work in a fast-paced, intellectually rigorous environment to tackle complex business challenges at scale. By harnessing the power of advanced analytics, data science, and machine learning, we create innovative, patentable solutions that transform customer experiences and drive the business forward. Team Overview: Machine Learning Experience (MLX) The MLX team leads Capital One s mission to build scalable, well-managed ML systems and platforms. We empower teams across the enterprise to develop, govern, and deploy machine learning models efficiently, securely, and at scale. From automated model governance to observability platforms, MLX enables end-to-end ML lifecycle management laying the foundation for AI-driven innovation across the organization. Role Overview We re looking for a Distinguished Engineer Machine Learning Engineering to join our MLX team. In this high-impact role, you'll architect and implement the platforms and tools that support model observability, automated governance, and ML model deployment at scale. This is an opportunity to drive enterprise-wide innovation and shape how ML is integrated into Capital One s core business systems. What You ll Do Design and build systems that capture and analyze large-scale model and feature metadata, including training metrics and runtime performance, to power model observability and governance automation. Partner with cross-functional teams including product managers, designers, and platform engineers to create scalable solutions that accelerate ML model lifecycle management. Lead efforts to enable automated governance decisions for ML models, ensuring compliance, auditability, and operational integrity. Architect and implement high-performance data pipelines that feed ML models with real-time and batch data. Contribute to the design and implementation of cloud-native ML systems using tools such as AWS, Kubernetes, and Terraform. Write clean, scalable, production-grade code in languages like Python, Go, or Java. Implement CI/CD pipelines, testing frameworks, and monitoring systems for ML applications. Drive the adoption of best practices in ML Ops, observability, and platform resilience. Basic Qualifications Master s Degree in Computer Science or related field. 15+ years of experience in software engineering or solution architecture. 10+ years building data-intensive, distributed computing systems. 10+ years programming in Python, Go, or Java. 8+ years of hands-on experience with industry-leading ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch, Dask, Spark). Preferred Qualifications PhD or Master's in Computer Science, Electrical Engineering, Mathematics, or related field. 5+ years of experience building, scaling, and optimizing production ML systems. Deep expertise in data preparation, feature engineering, and ML pipeline optimization. 10+ years writing performant, maintainable, and resilient production code. Strong experience deploying ML solutions on public cloud platforms (AWS, Azure, GCP). Expertise in distributed systems, file systems, or multi-node databases. Open-source contributor to ML tools or libraries. Published work in ML (papers, patents, blogs, etc.). 5+ years of experience in ML Ops (using MLflow, TFX, Kubeflow, etc.). Experience with LLMs and Generative AI applications (open-source or commercial models). Proven experience designing production-ready observability platforms for ML applications. Be at the forefront of building scalable, secure, and enterprise-grade ML platforms. Shape the future of AI and ML adoption in a top-tier financial institution. Collaborate with world-class engineers and data scientists. Solve real-world problems with high business impact. Thrive in a diverse, inclusive, and innovation-focused culture. Qualification : PhD or Master's in Computer Science, Electrical Engineering, Mathematics, or related field

Principal Associate Full Stack Engineering (GenAI Observability) Location: Bangalore Company: Capital One India About Us At Capital One India, we re tackling some of the most complex problems in financial services using machine learning, advanced analytics, and cloud-first engineering. Our mission is to build cutting-edge, patentable solutions that transform customer experiences, enhance operational efficiency, and ensure robust risk and compliance standards. We re a team of makers, breakers, doers, and disruptors obsessed with turning data into real-world impact at scale. About the Team Machine Learning Experiences (MLX) The MLX team is pioneering the future of model governance, ML observability, and Generative AI infrastructure at Capital One. We re enabling teams to seamlessly deploy ML and GenAI models at scale, with full visibility into performance, health, compliance, and ethical usage. This is the platform powering the next generation of AI-driven financial products across the company. About the Role We re looking for a Principal Associate Full Stack Engineer to lead the development of observability platforms for Generative AI systems. You ll be part of a cross-functional team focused on governance automation, LLM monitoring, and intelligent diagnostics using telemetry data, metadata, and advanced analytics. You ll design systems to collect, analyze, and visualize performance data from our large-scale GenAI infrastructure, helping data scientists and engineers make faster, safer decisions. What You ll Do Lead architecture and development of observability tools and dashboards for monitoring GenAI models and platform health. Design and build core APIs and SDKs to instrument large language models (LLMs) and foundational models (training, fine-tuning, prompting stages). Integrate Generative AI to enable observability features like anomaly detection, predictive analytics, and copilot-assisted troubleshooting. Partner with platform, MLOps, and governance teams to ingest and analyze telemetry, metadata, and runtime metrics at scale. Drive development of tools to ensure compliance with AI ethics, data governance, and industry regulations. Collaborate with product, design, and research to turn complex requirements into scalable, cloud-native software solutions. Lead proof-of-concept initiatives to test and showcase how GenAI can improve platform observability and decision-making. Contribute to the open-source community and stay at the forefront of GenAI and ML infrastructure evolution. Basic Qualifications Bachelor s or Master s degree in Computer Science, Engineering, or related field 4+ years of experience building distributed, data-intensive systems using microservices architecture 4+ years of experience in backend development with Python, Go, or Java 4+ years of expertise with observability stacks (Prometheus, Grafana, ELK) and adapting them for AI systems Strong knowledge of OpenTelemetry, and experience building custom SDKs and APIs 5+ years of hands-on experience with Generative AI models, especially applied to observability, governance, or compliance 2+ years of experience with cloud platforms such as AWS, Azure, or GCP Preferred Qualifications 4+ years building and optimizing ML systems in production environments 3+ years of experience with MLOps tools like MLflow, Kubeflow, or commercial platforms Experience with GenAI frameworks and libraries like LangChain, Haystack, and vector databases (FAISS, Chroma, OpenSearch) Familiarity with emerging observability tools for LLMs such as Langfuse, Phoenix, Helicone, or OpenInference Contributor to open-source GenAI or ML infrastructure projects Author or co-author of published work in AI/ML observability, governance, or performance monitoring Experience with PyTorch, TensorFlow, Spark, or Dask Knowledge of NVIDIA GPU telemetry, CUDA programming, and performance optimization for AI workloads Understanding of AI ethics, data governance, and regulatory frameworks for machine learning systems Why Join Capital One India Work at the intersection of technology, AI, and compliance helping shape the future of responsible AI Join a team driving enterprise-wide adoption of Generative AI Collaborate with world-class engineers, data scientists, and product leaders Enjoy a high-performance culture that encourages innovation, learning, and mentorship Access to cutting-edge tools, open-source contributions, and cloud-native infrastructure Qualification : Bachelors or Masters degree in Computer Science, Engineering, or related field

Role: Senior Analyst Machine Learning Performance & Testing Location: Bengaluru, Karnataka, India Experience: 3 5 Years Employment Type: Permanent, Full-Time About the Role We are seeking a skilled and detail-oriented Senior Analyst with strong experience in ML model performance testing, load testing, and end-to-end (E2E) automation. This role is focused on ensuring scalable, low-latency deployment of production-grade machine learning models. The ideal candidate will be proficient in evaluating model performance under varied workloads, building robust test frameworks, and enhancing system monitoring. Key Responsibilities Conduct load testing and performance benchmarking for machine learning models under varying requests per second (RPS) scenarios. Develop and automate end-to-end test cases to validate model readiness and support smooth rollouts. Monitor and improve model scalability, response time, and error rates across production environments. Collaborate with ML engineers, backend developers, and QA test teams to ensure seamless integration and testing workflows. Identify and address bottlenecks in model inference, helping improve performance for high-volume, low-latency applications. Set up alerting and observability pipelines for model health using industry-standard tools. Required Skills & Tools Performance Testing & Monitoring: ML Load Testing, Job Monitoring, Model Scalability Evaluation Platforms & Tools: Databricks, MLflow, Seldon, Kubeflow, Tecton, Jenkins Cloud Services: Experience with AWS and deploying/testing models in cloud environments Programming Languages: Proficiency in at least one of the following Python, Java, Scala Experience: Working with production-level ML models, especially involving high data volumes and real-time inference Strong communication skills and ability to work in cross-functional teams Preferred Qualifications Hands-on experience with CI/CD pipelines for ML systems Knowledge of A/B testing and canary deployments for ML models Experience building testing frameworks for ML infrastructure at scale Understanding of monitoring and alerting best practices in production ML systems Be at the forefront of ML operations and model performance optimization Collaborate with industry-leading engineers and contribute to cutting-edge AI deployments Gain deep exposure to real-time data systems, cloud platforms, and enterprise-scale ML testing Competitive compensation and an innovative, fast-paced work environment

Staff Software Engineer - Networking Location: Bengaluru, India Company: Databricks About Databricks Databricks powers the world s best data and AI infrastructure platform, enabling data teams to tackle critical problems from transportation innovation to medical breakthroughs. Our platform unifies data, analytics, and AI for over 10,000 organizations worldwide, including more than half of the Fortune 500. Founded by the creators of Apache Spark , Delta Lake, and MLflow, Databricks is headquartered in San Francisco with global offices. Role Overview As a founding member of our new Networking Infrastructure team in Bengaluru, you will design and develop backend connectivity services that power millions of VMs running on Databricks. This platform connects our control plane to the compute plane, enhancing scalability and optimizing cloud resource usage. You ll collaborate closely with product management, operations, and engineering teams to deliver robust, scalable, and efficient networking solutions. This is an exciting hands-on leadership role for an experienced engineer passionate about multi-cloud and distributed systems challenges. What You ll Do Lead design and development of new networking services powering connectivity between control and compute planes. Build scalable backend connectivity systems supporting millions of virtual machines. Collaborate cross-functionally with product, operations, and engineering teams. Solve complex multi-cloud and distributed systems problems in a fast-paced environment. Contribute to setting up and growing the Bengaluru networking team from scratch. What We Look For 12+ years of production software engineering experience in Python, Java, Scala, C++, or similar. 7+ years building large-scale distributed systems from the ground up. Extensive experience in networking domain and SaaS platforms or Service-Oriented Architectures. Strong leadership and hands-on engineering skills. Passion for solving novel challenges in multi-cloud networking and distributed systems. Benefits Comprehensive benefits package tailored to employee needs. Inclusive and diverse workplace committed to equal opportunity for all. Diversity & Inclusion Databricks is dedicated to fostering a diverse and inclusive culture where all employees can thrive. We uphold equal employment opportunities without regard to age, race, gender, ethnicity, disability, religion, sexual orientation, veteran status, or any other protected characteristic.

Staff Software Engineer Databases Location: Bengaluru, India Company: Databricks About Databricks Databricks is a leading data and AI company powering over 10,000 organizations globally, including half of the Fortune 500. Founded by the original creators of Apache Spark , Delta Lake, and MLflow, Databricks offers a unified platform for data, analytics, and AI, enabling enterprises to innovate with confidence. With its global presence and a growing Bengaluru team, Databricks is rapidly expanding. Role Overview As a Staff Software Engineer in Bengaluru, you ll work within Backend or Distributed Data Systems (DDS) teams to build scalable, reliable, and high-performance services powering Databricks data and AI platform. You will tackle challenges ranging from distributed systems and cloud storage to service architecture, workflow orchestration, and developer experience. Key Responsibilities Develop large-scale distributed backend services, including managing cloud storage backends like AWS S3 or Azure Blob Store. Build and maintain infrastructure that supports millions of cluster-hours per day. Contribute to key DDS projects such as Apache Spark , Delta Lake, and performance engineering. Design and implement high-performance, reliable, and scalable systems and client libraries. Collaborate cross-functionally to drive innovation in cloud-native data processing and storage. Qualifications BS or higher in Computer Science or related field. 10+ years of production software engineering experience in Python, Java, Scala, C++, or similar. Proven experience developing large-scale distributed systems from the ground up. Experience with SaaS platforms or Service-Oriented Architectures. Benefits & Culture Competitive benefits tailored to employees needs. Committed to fostering a diverse, inclusive, and equitable work environment. Diversity & Inclusion Statement Databricks ensures equal employment opportunities regardless of age, race, gender, ethnicity, disability, sexual orientation, veteran status, or other protected characteristics, striving for a welcoming and inclusive workplace. Qualification : BS or higher in Computer Science or related field.

Delivery Solutions Architect Location: Bengaluru, India Company: Databricks Role Overview As a Delivery Solutions Architect (DSA) at Databricks, you will be the key technical leader post-sale, collaborating closely with sales, field engineering, and product teams to accelerate adoption and maximize value for complex, strategic customers. You will lead technical account strategies, drive onboarding and enablement, troubleshoot issues, and ensure successful production rollout and healthy consumption of Databricks workloads. Key Responsibilities Partner with Solutions Architects to understand customer use cases and demand plans. Own and execute technical strategies for prioritized customers and use cases. Serve as the primary technical point-of-contact post-sale for key accounts, managing multiple use cases. Coordinate internal Databricks resources and escalate issues as needed to ensure customer success. Develop and manage execution plans covering onboarding, user enablement, product adoption, and governance. Provide regular updates on customer health, usage KPIs, risks, and product adoption to senior leadership. Collaborate with Professional Services for engagement proposals and delivery. Navigate product and engineering teams to incorporate new innovations and upgrades. Qualifications & Experience 8+ years of technical project/program delivery experience in Data and AI domains. Proficiency in Python, SQL, or Scala programming. Customer-facing experience in pre-sales, technical architecture, customer success, or consulting roles. Strong understanding of distributed data systems architecture and how to link business value to project outcomes. Skilled in managing technical escalations, stakeholder management, and strategic roadmap development. Demonstrated track record of meeting or exceeding goals/quotas. Bachelor s degree in Computer Science, Information Systems, Engineering, or equivalent experience. Willingness to travel up to 30%. About Databricks Databricks is a leading data and AI company that powers thousands of organizations worldwide with its unified Data Intelligence Platform. Founded by the creators of Apache Spark , Delta Lake, and MLflow, Databricks empowers enterprises to innovate with data and AI. Qualification : Bachelors degree in Computer Science, Information Systems, Engineering, or equivalent experience.

Engineering Leader - Machine Learning Location: Bangalore, Karnataka, India Employment Type: Full-Time | Hybrid Work Model About Eightfold.ai At Eightfold.ai, we re revolutionizing the future of employment by leveraging artificial intelligence to connect individuals to the right career opportunities based on their skills, not just their network. Our AI-powered Talent Intelligence Platform is transforming how organizations plan, hire, develop, and retain a diverse workforce. With $410M+ in funding and a $2B+ valuation, we re growing rapidly, and if you're passionate about solving one of society's most critical challenges employment then Eightfold is the place for you. Led by visionary leaders like Ashutosh Garg (former Google Search and Personalization leader) and Varun Kacholia (former Facebook and Youtube leader), we are shaping the future of AI-powered talent management. About the AI Platform Team Our AI/ML team is the heart of Eightfold, pushing the boundaries of applied machine learning. We re working with massive datasets, solving complex problems, and building cutting-edge AI models that are reshaping how companies approach talent management. Join us if you re eager to work in a team where every day presents a new challenge and opportunity. What You ll Do As the Engineering Leader - Machine Learning, you ll be responsible for leading and mentoring a high-performing team of engineers, driving the success of AI-driven products at Eightfold. Your primary responsibilities will include: Team Leadership: Coach, mentor, and manage a talented team of engineers to foster a culture of innovation, collaboration, and high performance. ML Model Ownership: Lead the development and deployment of cutting-edge deep learning models across all Eightfold products, ensuring reliability, scalability, and high-quality performance. Platform Development: Help build high-performance, flexible infrastructure that supports a variety of deep learning techniques and modeling approaches. End-to-End ML Pipeline: Oversee the end-to-end process of building and deploying machine learning models, including creating robust data pipelines that can process unstructured data. ML Framework Implementation: Design and implement an intuitive ML development framework that ensures efficiency and ease of use for data scientists and engineers. Model Fairness: Work with our internal model fairness platform to ensure that we are providing equal opportunity for everyone through responsible ML practices. Cross-Team Collaboration: Work closely with product teams to apply deep learning techniques to solve complex business problems across various domains. What You Should Already Know To be successful in this role, you should have: Strong Foundation in ML & Deep Learning: Expertise in applying Natural Language Processing (NLP) and deep learning solutions to solve real-world problems. Experience with Language Models: Familiarity with advanced language models such as BERT, GPT-3, T5, and others. Academic Background: A BS, MS, or PhD in Computer Science, Data Science, Mathematics, or related fields. Proven ML Experience: Hands-on experience building and deploying machine learning models at scale, particularly in production environments. Programming Expertise: Strong knowledge of ML languages such as Python, C++, Java, R, Scala, and experience with scientific libraries like numpy, pandas, and frameworks like TensorFlow, PyTorch, scikit-learn, etc. Strong ML Theory Knowledge: In-depth understanding of ML theory and experience working with large-scale datasets, data ingestion, and processing systems. Experience with Distributed Systems: Familiarity with distributed systems, including REST APIs, microservices, and data processing frameworks. Metrics-Focused: A passion for building high-quality models that deliver results and metrics-driven outcomes. Nice to Have Real-Time Tech Problems: Experience with real-time processing or low-latency systems. Cloud Environments: Familiarity with cloud platforms like AWS, and experience using cloud-based ML tools. MLOps Tools & Pipelines: Experience with MLflow, Metaflow, or similar tools to streamline ML workflows and operations. Advanced Tech Stack: Familiarity with tools like Spark, MLlib, Databricks, Apache Airflow, etc. Impactful Work: Join a company dedicated to solving one of society's most pressing issues employment. Your work will have a direct impact on individuals' careers around the world. Innovation at Scale: Work with cutting-edge AI and ML technologies to shape the future of talent management. Competitive Compensation: Receive an attractive salary, equity, and comprehensive benefits package (including family medical, vision, and dental coverage). Collaborative Environment: Work in a culture that values transparency, ownership, and collaboration across teams. Hybrid Work Model: Enjoy a hybrid work environment, with flexibility for remote work and in-office collaboration at our Bangalore office. Growth Opportunities: Be part of a rapidly scaling company with vast opportunities for career development and leadership roles. Equal Opportunity Employer Eightfold.ai is an Equal Opportunity Employer. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, or disability. If you are an experienced and visionary leader in Machine Learning, eager to make a lasting impact while solving one of society's most important challenges, we would love to hear from you. Qualification : BS or MS or PhD degree in Computer Science, Data Science or Mathematics

AI Platform Architect Location: Bangalore, Karnataka, India Employment Type: Full-Time About Adobe Adobe is changing the world through digital experiences. Whether you're an emerging artist or a global brand, our tools empower creativity and innovation across every screen. From powerful imaging and video solutions to immersive web and app design, Adobe s mission is to help people and businesses deliver exceptional digital experiences. We are committed to creating an inclusive workplace where everyone is respected and given equal opportunity. Innovation can come from anywhere and the next big idea could be yours. Job Description We are looking for a visionary AI Platform Architect with deep expertise in building and scaling cloud-native, AI-powered platforms. The ideal candidate will have experience deploying large-scale, customer-facing AI solutions and a deep understanding of modern cloud architecture, data systems, MLOps, and LLMOps. Responsibilities Design and develop scalable AI/ML platforms and pipelines across AWS, Azure, and GCP. Architect end-to-end LLM pipelines including model training, fine-tuning, serving, inference APIs, and monitoring. Lead cross-functional teams in delivering AI solutions from experimentation to production. Implement MLOps and LLMOps best practices using tools like MLFlow, SageMaker, Langchain, and LangGraph. Design GPU-optimized architectures for training and inference of LLMs using DeepSpeed, vLLM, and other modern frameworks. Support infrastructure automation and container orchestration with Kubernetes, Docker, and CI/CD pipelines. Collaborate with internal stakeholders and clients to understand requirements, evangelize platform solutions, and ensure successful delivery. Key Skills and Expertise Cloud and DevOps: Expertise in AWS, Azure, GCP especially VPC design, cloud databases, and serverless architecture. Certified in AWS Professional Solution Architect, AWS ML Specialty, or Azure Solutions Architect Expert (preferred). Proficient with Kubernetes, Docker, FluentD, Kibana, Grafana, Prometheus. Data and Streaming: Experience with OLTP/OLAP databases and cloud-native data warehouses like BigQuery, Aurora, Spanner. Hands-on with Kafka, Apache Flink, Spark, Airflow, Databricks, Apache Iceberg, Presto. AI/ML & LLM Expertise: In-depth understanding of LLMs (GPT, Gemini, Claude, Mixtral, Llama, Hugging Face OSS models). LLMOps frameworks: Langchain, Langgraph, Langflow, Flowise, LLamaIndex. ML lifecycle tools: MLFlow, SageMaker, Vertex AI, Azure AI, AWS Bedrock. Proven experience in model optimization, fine-tuning, and high-throughput inference systems. Programming Languages: Proficient in Python, SQL, and JavaScript. Preferred Qualifications 10+ years in cloud and AI/ML platform architecture roles. Experience delivering AI solutions for enterprise-scale clients. Hands-on experience with GPU architecture and parallel/distributed training. Strong communication skills with ability to influence technical and business stakeholders. Work on cutting-edge AI technologies and shape future product experiences used by millions. Collaborate with world-class engineers and scientists in a diverse, inclusive culture. Be part of a company that values creativity, innovation, and employee well-being. Adobe is proud to be an Equal Opportunity Employer. We welcome and encourage candidates from all backgrounds to apply.

Machine Learning Engineer Full-Time - Bengaluru, India - Data Science / Artificial Intelligence / Engineering Join our dynamic Data Science / Artificial Intelligence / Engineering team in Bengaluru, India as a Full-Time Machine Learning Engineer and play a key role in driving data-driven innovation! We are seeking a skilled and results-oriented Machine Learning Engineer to design, build, and deploy scalable machine learning models that address real-world business challenges. You will collaborate closely with data scientists, engineers, and product managers to transform raw data into actionable insights and integrate intelligent features into our products. As a Machine Learning Engineer, you will be responsible for the complete lifecycle of machine learning models and pipelines, from design and development to seamless deployment for a variety of applications. This includes classification, regression, clustering, recommendation systems, and time-series forecasting. You will leverage your expertise to preprocess and analyze large and complex datasets, extracting meaningful features and valuable insights. Collaboration with cross-functional teams will be crucial as you identify strategic ML opportunities and define clear success metrics. A key aspect of this role involves optimizing machine learning models for peak performance, scalability, and accuracy within production environments. You will build robust APIs or efficient microservices to integrate these models seamlessly into our applications, utilizing tools such as Flask or FastAPI. Continuous improvement is paramount, and you will be responsible for the ongoing monitoring and retraining of models based on their performance and any signs of data drift. Staying at the forefront of the field is essential, and you will be expected to stay updated with the latest ML research and emerging technologies, applying them to continuously enhance our product capabilities. Key Responsibilities: Design, develop, and deploy machine learning models and pipelines for diverse applications including classification, regression, clustering, recommendation, and time-series forecasting. Preprocess and analyze large datasets to extract meaningful features and actionable insights. Collaborate effectively with cross-functional teams to identify strategic ML opportunities and define clear success metrics. Optimize models for maximum performance, scalability, and accuracy in production environments. Build robust APIs or efficient microservices to integrate ML models into applications using tools like Flask or FastAPI. Continuously monitor and retrain models based on performance metrics and potential data drift. Stay updated with the latest ML research and technologies and apply them to enhance product capabilities. Minimum Qualifications: Bachelor s or Master s degree in Computer Science, Data Science, Statistics, or a related field. 2+ years of proven experience as a Machine Learning Engineer or in a similar role. Strong proficiency in Python and key ML libraries such as Scikit-learn, XGBoost, TensorFlow, or PyTorch. Practical experience working with both SQL and NoSQL databases. Solid knowledge of essential data preprocessing, effective feature engineering, and robust model evaluation techniques. Familiarity with standard software engineering practices, including version control (Git), thorough code reviews, and efficient CI/CD pipelines. Preferred Qualifications: Prior experience with deep learning, natural language processing (NLP), or computer vision. Familiarity with major cloud services like AWS, GCP, or Azure (especially SageMaker, Vertex AI, etc.). Understanding of modern MLOps tools and practices (e.g., MLflow, Kubeflow, DVC). Practical experience with containerization and orchestration tools (Docker, Kubernetes). Knowledge of big data tools (e.g., Spark, Hadoop) is considered a significant plus. What We Offer: Competitive salary and performance-based incentives to reward your contributions. Comprehensive health insurance and valuable wellness benefits to support your well-being. Dedicated learning and development programs for continuous professional growth. Exciting opportunities to work on impactful, real-world AI/ML projects with significant scale. A collaborative, inclusive, and innovative work culture that fosters teamwork and creativity. Flexible working hours and a hybrid work model to promote a healthy work-life balance.

Position: Senior Data Scientist Location: Bangalore Employment Type: Full-time Experience Required: 5 to 7 years Purpose of the Position: The Senior Data Scientist will play a key role in designing, developing, and implementing machine learning models and algorithms to solve complex business problems. The role involves collaborating with data scientists, software engineers, and business stakeholders to deliver scalable, efficient machine learning solutions that drive innovation and improve business outcomes. Key Responsibilities: Model Development and Optimization: Develop, train, and optimize machine learning models to meet business objectives. Ensure models are accurate, efficient, and scalable. Data Pipeline and Infrastructure: Design and maintain robust data pipelines to support machine learning workflows. Ensure data quality and integrity throughout the data lifecycle. Deployment and Monitoring: Deploy machine learning models into production. Monitor model performance and implement improvements as needed. Collaboration and Communication: Work with cross-functional teams to understand business requirements and translate them into technical solutions. Communicate complex technical concepts to non-technical stakeholders. Research and Innovation: Stay up to date with the latest advancements in machine learning and AI. Experiment with new techniques and technologies to enhance the organization's capabilities. Essential Skills: Machine Learning Frameworks: Experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. Programming Languages: Strong skills in Python and R. Data Processing: Experience with tools like Pandas, NumPy, and Spark. Model Deployment: Experience with Docker, Kubernetes, MLflow, and FastAPI. Databases: Strong experience in databases like Snowflake, MongoDB, and Cosmo DB. Statistical Analysis: Strong foundation in statistics and probability. Model Management: Experience establishing model management, monitoring, support, and maintenance frameworks. ML Lifecycle: Experience setting up ML lifecycle processes and governance policies, as well as providing L0, L1, and L2 support. Desired Skills: Deep Learning: Familiarity with deep learning frameworks like TensorFlow or PyTorch. Natural Language Processing (NLP): Understanding of NLP techniques and applications. Cloud Computing: Experience with cloud platforms like AWS, Azure, or Google Cloud. Big Data Technologies: Knowledge of big data technologies such as Hive, Pig, or Cassandra. Software Engineering: Proficiency in software development and version control systems like Git. Qualifications: Education: Master's degree or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field. Experience: Over 5 years of experience in machine learning, with a proven track record of developing and deploying models. Certifications: Relevant certifications in machine learning or data science are a plus. Key Qualities: Analytical Thinking: Strong analytical and problem-solving skills. Communication: Excellent verbal and written communication skills. Team Player: Ability to work effectively in a collaborative team environment. Adaptability: Flexibility to adapt to changing business needs and technologies. Innovation: A proactive approach to exploring new ideas and technologies. Apply now to join our dynamic team and lead innovation through machine learning and AI! Qualification : Master's degree or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field.

Job Title: Senior Solutions Engineer (Analytics, AI, Big Data, Public Cloud) Job Summary As a Senior Solutions Engineer (Analytics, AI, Big Data, Public Cloud), you will guide the technical evaluation phase in a hands-on environment throughout the sales process. You will be a technical advisor internally to the sales team and work with the product team as an advocate of your customers in the field. You will help our customers achieve tangible data-driven outcomes through the use of our Databricks Lakehouse Platform, helping data teams complete projects and integrate our platform into their enterprise Ecosystem. You'll grow as a leader in your field while finding solutions to our customers' biggest challenges in big data, analytics, data engineering, and data science problems. You will report to the Solutions Architect (SA) Manager. The Impact You Will Have You will be a Big Data Analytics expert on aspects of architecture and design. Engage with the technical community by leading presentations, workshops, seminars, and meet-ups. Lead your clients through evaluating and adopting Databricks, including hands-on Spark programming and integration with the wider cloud ecosystem. Support your customers by authoring reference architectures, how-tos, and demo applications. Integrate Databricks with 3rd-party applications to support customer architectures. Together with your Account Executive, you will form successful relationships with clients throughout your assigned territory to provide technical and business value. What We Look For Consulting, pre-sales, or post-sales experience working with external clients across a variety of industry markets. Core strength in either data engineering or data science is advantageous. 5+ years of experience demonstrating technical concepts, including presenting and white-boarding. 4+ years of experience designing architectures within a public cloud (AWS, Azure, or GCP). 4+ years of experience with Big Data technologies, including Spark, AI, Data Science, Data Engineering, Hadoop, Cassandra, and others. Solid coding experience in Python, R, Java, Spark, or Scala. About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake, and MLflow. To learn more, follow Databricks on Twitter, LinkedIn, and Facebook.

Job Title: Cash Application Analyst Job Summary We are looking for an experienced Cash Application Analyst to manage and optimize the cash application process at our tech company, which operates on a usage-based billing model. The ideal candidate will ensure the accurate and timely application of customer payments to invoices, contribute to efficient cash flow management, and collaborate with key stakeholders to enhance processes. This role requires a meticulous professional with strong analytical skills, experience in high-volume cash application environments, and an ability to navigate in a fast-paced environment. This position will be catering to the US (EST) timezone. The Impact You Will Have Oversee the daily cash application process, ensuring customer payments are accurately and promptly applied to invoices. Monitor and reconcile incoming payments across multiple payment channels, including ACH, wire transfers, credit card transactions, and checks. Collaborate closely with the billing and collections teams to resolve discrepancies and support seamless end-to-end cash management. Develop and implement cash application policies and procedures that align with the unique aspects of a usage-based billing system. Identify and address payment discrepancies, customer account issues, and unapplied cash, facilitating timely resolutions. Maintain and update comprehensive documentation of cash application processes and customer payment records. Generate reports on cash application metrics, providing actionable insights to senior finance leadership. Participate in system enhancements and software implementations to improve cash application automation and efficiency. Liaise with the customer support team to handle customer inquiries related to payments and account reconciliations. Drive continuous process improvements and leverage technology to enhance accuracy, reduce processing times, and streamline operations. Ensure compliance with company policies and relevant financial regulations. What We Look For Bachelor s degree in Finance, Accounting, Business Administration, or a related field preferred. Minimum of 4 years of experience in cash application, accounts receivable, or related financial operations. Strong understanding of usage-based billing models and associated financial processes. Excellent attention to detail and problem-solving skills. Proficiency with ERP systems and payment processing platforms; experience with NetSuite and Salesforce is a plus. Strong analytical skills with the ability to interpret data and generate reports. Effective communication and interpersonal skills for collaboration with cross-functional teams. Operate in a fast-paced environment with tight deadlines. Ability to adapt to evolving business needs and drive change management. About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake, and MLflow. To learn more, follow Databricks on Twitter, LinkedIn, and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Qualification : Bachelors degree in Finance, Accounting, Business Administration, or a related field preferred.

Job Title: Senior Revenue Operations Analyst Job Summary We are seeking an experienced Senior Revenue Operations Analyst to join our team. You will support the daily Order to Cash operations supporting the global revenue accounting operations and revenue close process. You will play an essential role in data integrity; ensuring all customer, opportunity, and subscription information is accurate and reportable. You will partner with other teams to create and promote a scalable order to cash process. This will be the first hire for the site! The Impact You Will Have Analyze signed contracts and completed orders for completeness, accuracy, and compliance with company bookings and revenue recognition guidelines. Partner with Sales, Deal Desk, Renewals, Collections, Legal, and Revenue teams to develop expertise in order-to-cash policies and procedures. Create and maintain detailed records in our ERP and billing platform to support billing, commissions, forecasting, and revenue recognition processes, adhering to internal service level agreements. Generate and maintain comprehensive documentation of policies and processes, and assist in identifying process improvement and automation opportunities. Execute month-end accounting and reporting activities, ensuring timely and accurate financial close processes. Document controls and procedures for both new and existing business models to maintain compliance and operational excellence. Manage special projects as assigned, delivering accurate and timely results. Provide audit support for both control and substantive testing, ensuring compliance with internal and external requirements. Collaborate on process and system implementation and enhancement projects, assisting with user acceptance testing (UAT) as needed. Proactively identify areas for process optimization, recommending and implementing best practices for efficiency and scalability. Ensure data integrity and accuracy within financial systems by performing regular reviews and audits. Partner with the finance transformation, IT, and engineering teams to streamline revenue operations processes. What We Look For Bachelor s degree in Finance, Accounting, Business Administration, or a related field preferred. Minimum of 6 years of revenue operational accounting experience. Strong accounting background with experience in revenue operational accounting and financial close processes. Strong understanding of usage-based billing models and associated financial processes. Proficiency with ERP systems and payment processing platforms; experience with a global ERP such as NetSuite and Salesforce is required. High level of analytical skills with the ability to interpret large datasets, generate reports, and perform complex reconciliations using spreadsheet software (e.g., Excel, Google Sheets). Effective communication and interpersonal skills for collaboration with cross-functional teams. About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake, and MLflow. To learn more, follow Databricks on Twitter, LinkedIn, and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Qualification : Bachelors degree in Finance, Accounting, Business Administration, or a related field preferred.

Job Title: Usage Manager Job Summary We are seeking an experienced Usage Manager to join our team. You will support the daily Order to Cash operations by helping lead the global revenue accounting operations and revenue close process. You will play an essential role in data integrity; ensuring all customer usage information is accurately reportable. You will partner with other teams to create and promote a scalable order to cash process. This is an individual contributor position, and will be the first hire in India! The Impact You Will Have Lead and manage a team of Revenue Operations Analysts, including performance management, coaching, and development. Manage escalations related to order-to-cash processes, ensuring timely resolution and communication with stakeholders. Monthly metrics highlighting performance against agreed SLAs and KPIs. Maintain and/or create detailed SOPs for all processes. Prepare proposed usage adjustments and credits, when applicable. Analyze usage for signed contracts with assurance to accuracy and compliance with company revenue recognition guidelines. Partner with Sales, Deal Desk, Billing, Engineering, IT, Legal, and Revenue Teams to develop expertise in order-to-cash policies and procedures specific to usage. Create and maintain detailed records in our ERP and billing platform NetSuite/Metronome to support billing, commissions, forecasting, sales, and revenue recognition processes, adhering to internal service level agreements. Generate and maintain comprehensive documentation of policies and processes, and assist in identifying process improvement and automation opportunities. Execute month-end accounting and reporting activities, ensuring timely and accurate financial close processes. Document controls and procedures for both new and existing business models to maintain compliance and operational excellence. Manage special projects as assigned, delivering accurate and timely results. Change management or SOPs with any system enhancements. Provide audit support for both control and substantive testing, ensuring compliance with internal and external requirements. Collaborate on process and system implementation and enhancement projects, assisting with user acceptance testing (UAT) as needed. Proactively identify areas for process optimization, recommending and implementing best practices for efficiency and scalability. What We Look For Bachelor s degree in Finance, Accounting, Business Administration, or a related field preferred. Minimum of 8 years of revenue operational accounting experience, with demonstrated experience leading and managing teams. Strong understanding of usage-based billing models and associated financial processes. Proficiency with ERP systems and payment processing platforms; experience with a global ERP such as NetSuite and Salesforce is required. High level of analytical skills with the ability to interpret large datasets, generate reports, and perform complex reconciliations using spreadsheet software (e.g., Excel, Google Sheets). Ability to adapt to evolving business needs and drive change management. Must be adaptive to change. Proven ability to manage team performance, provide constructive feedback, and foster a positive and productive team environment. About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake, and MLflow. To learn more, follow Databricks on Twitter, LinkedIn, and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Qualification : Bachelors degree in Finance, Accounting, Business Administration, or a related field preferred.

Job Title: Data Engineer Job Summary As a Data Engineer in the IT team, you will work on various big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help business to get most value out of their data. The Impact You Will Have You will work on a variety of impactful Big Data projects which may include building reference architectures, how-to's and production grade MVPs. Work on implementing transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications. Work on architecture and design; bootstrap or implement strategic projects. What We Look For 7+ years experience with Big Data Technologies such as Apache Spark , Kafka, Cloud Native and Data Lakes. 4+ years of experience working on Big Data Architectures independently. Preferred experience working in the Databricks ecosystem. Comfortable writing code in either Python or Scala. Experience working across Cloud Platforms (GCP / AWS / Azure). Documentation and white-boarding skills. Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects. About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake, and MLflow. To learn more, follow Databricks on Twitter, LinkedIn, and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks.

CSQ124R98 At Databricks, an Incident Manager utilizes their technical experience and resourcefulness to lead urgent customer situations to resolution. Responsible for managing frequent, high-quality updates to all internal and external stakeholders, Incident Managers advocate with engineering and leadership, on behalf of their customers, to ensure that escalations are handled with the appropriate level of urgency from stakeholders. The impact you will have: Drive critical customer escalations or widespread outages to conclusion and resolution. Escalate to on-call resources in support and engineering and establish checkpoint calls and action items to ensure that progress is made and status updates are delivered on time. Demonstrate cross-functional leadership while establishing ownership of escalations and outages. Compile and deliver frequent high-quality communications to internal and external stakeholders, including executive staff. Candidate should be comfortable creating concise and effective messaging that is tailored to a technical or executive audience with minimal assistance from others. Commence and lead war rooms while establishing other temporary communication channels as warranted for the duration of an outage. Ability to multi-task on several incidents and/or projects at once. Be a leader who identifies product and process improvements from every incident and submits necessary feedback for improvements. Participate in on-call rotations. What we look for: Minimum 8+ years of experience in customer support, support escalation and incident management is required. Excellent contextual interpretation and writing skill with an effective ability to summarize and communicate to technical and business audiences is required. Demonstrates strong ability to make timely decisions for both business and technical perspectives. Excellent analytical and troubleshooting skills are required. Candidate should be able to demonstrate technical excellence by applying engineering principles to solve complex problems. Hands-on experience developing any two or more of the following: Big Data, Hadoop, Spark, Machine Learning, Artificial Intelligence, Streaming, Kafka, Data Science, ElasticSearch related industry use cases at the production scale. Hands-on experience in the performance tuning/troubleshooting of Spark-based applications at production scale. Proven and real-time experience in JVM and Memory Management techniques such as Garbage collection and Heap/Thread Dump Analysis is required. Working knowledge in Data Lakes and preferably on the SCD types use cases at production scale. Working and hands-on experience with any SQL-based databases, Data Warehousing/ETL technologies like Informatica, DataStage, Oracle, Teradata, SQL Server and MySQL Linux/Unix administration skills and hands-on experience with AWS or Azure or GCP is required. About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake and MLflow. To learn more, follow Databricks on Twitter,LinkedIn and Facebook . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visithttps://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.