Neural Networks Jobs in Pallavaram

Deep Learning Engineer-1 Job Description: As a Deep Learning Engineer-1, you will be responsible for developing Computer Vision (CV) Deep Learning models with a long-term view of integrating them with various Detect products. You will also be expected to take ownership of the data preparation and processing pipelines and innovate on faster ways to use the same. We are looking for Candidates capable of handling oneself in a technically diverse and demanding atmosphere. Job Responsibilities: Train Deep learning models Ensuring that best practices are followed in solving AI problems including thorough problem analysis, prior research understanding, persistent experimentation and documentation, rapidprototyping, and extensive testing. Creating and executing on processes for thorough performance evaluation of the solution against real-world test cases. Benchmarking against competing solutions, prior research and customer s acceptance criteria wherever applicable. Data Management Planning the nature, volume and source of data required to effectively solve the problem. Ideating with relevant people on best ways to source and annotate this data. Following up with Labelling Teams on a continual basis to ensure minimal rework. Others Good articulation of your thoughts and the ability to write technical documentation and blog posts. To be able to contribute back to open-source libraries and integrate with their testing mechanisms when required. Requirements: Adapt at modelling Computer Vision problems using Deep Learning frameworks. Adapt at using git and using IDEs. Projects, certification, or open-source work showing experience in using deep learning for Computer Vision and Data Management. 1+ years work experience in computer vision; key areas of interest include object detection, image/ video, tracking and recognition, OCR detection, activity recognition. Preferred Skills & Knowledge: Experience in Docker. Experience in Nvidia frameworks like TAO, Deepstream, TensorRT. Experience in fields relating to Image Stitching, 3-D reconstruction, video analysis, clustering, object detection, image classifications, semantic image segmentation, Large Vision Models (LVM), Large Language Models (LLM), LlamaIndex, LangChain, RAG. Knowledge/Experience on deploying programs into compute limited hardware like RPi/Nvidia Jetson. Strong understanding of theory behind DL techniques such as CNNs, transformers, LLM/LMM supervised and unsupervised Learning, optimization techniques, etc.

Platform Engineer Job Description: We are seeking a highly skilled and motivated Platform Engineer to join our talented engineering team. As a Platform Engineer, he/she will play a critical role in designing, developing, and maintaining the scalable, reliable, and secure platform that powers our advanced industrial solutions. You will work closely with cross-functional teams to ensure our platform meets the evolving needs of our customers and supports the deployment of our AI-driven technologies. Responsible for developing batch automations, CI/CD Pipeline. Hands on experience with cloud service providers, mainly AWS and Azure. Working knowledge in database management for SQL and NoSQL databases. Ability to convert the user stories into enterprise level software solutions. Should be capable of setting up Agile processes within the team for continuous monitoring of the system. Experience in working with Monolithic and Microservice architecture and taking on complex projects. Working knowledge in backend frameworks like Django/Flask is an added advantage. Ability to collaborate with other teams to provide first time right solutions. Hands on knowledge of Unit Testing frameworks with code coverage and software testing tools. Can design larger systems, work effectively across multiple teams to deliver large projects, and leads the team to technical success. It has shown soft skills and political acumen and can negotiate across teams. Proven to make ace design decisions and be fool proof when debugging. Been thought to be extremely reliable. Work independently. Involved in periodic code reviews with the team. Key Responsibilities: Design and Development: Architect, design, and develop scalable and high-performance platform components. Design application using SOLID principles. Implement robust APIs and services to support application integration and data processing. Collaborate with software engineers, data scientists, and product managers to understand requirements and deliver effective solutions. Platform Maintenance: Ensure the reliability, security, and performance of the platform through continuous monitoring and improvement. Implement best practices for system health monitoring, logging and monitoring system. Perform regular system updates, patches, and security enhancements. Automation and Infrastructure: Develop and maintain infrastructure as code (IaC) to automate the deployment and management of platform resources. Optimize CI/CD pipelines to streamline development workflows and reduce deployment times. Implement and manage containerization and orchestration technologies (e.g., Docker, Kubernetes). Collaboration and Support: Work closely with the Product and Delivery team to align platform capabilities with operational needs. Independently collaborate with other engineering teams to address and resolve platform-related issues. Innovation and Continuous Improvement: Stay up-to-date with emerging technologies and industry trends. Propose and implement improvements to enhance platform functionality, performance, and scalability. Participate in code reviews, design discussions, and team meetings to foster a culture of innovation and excellence. Requirements: Education: Bachelor s/master s degree in computer science engineering Experience: 1+ years of experience in Platform Engineering Technical Skills: 1+ experience as a Platform Engineer. Strong knowledge in Python, Go lang, Django and Flask framework. Strong knowledge in Git. Good Knowledge in RDBMS/No SQL. Good knowledge in JIRA, PyUnito. Basic knowledge in Linux and Linux commands. Experience with cloud platforms (AWS, Azure, GCP). Hands-on experience with containerization (Docker) and orchestration (Kubernetes). Solid understanding of networking, security, and database management. Good to have knowledge of AI. Qualification : Bachelors/masters degree in computer science engineering