Senior Ai / Ml Engineer Job in Blueshift Labs

Blueshift is looking for bold and self-motivated data science engineers to join the team. You will have a chance to work on all aspects of big fast data systems, state-of-the-art cloud infrastructure, and cutting-edge AI algorithms.

What are examples of work that Data science Engineers have done at Blueshift?

• AI Products: AI/ML engineers have developed and owned end-to-end AI products including AI studio dashboards, data pipelines, feature engineering, AutoML systems, inference services. We have designed and set up our data science stack for any AI/ML engineer to set up a new end-to-end AI product in weeks/months.
• AI algorithms: We have developed cutting-edge AutoML predictive models and state-of-the-art recommender systems to deliver the right content, to the right audience, on the right channel, at the exact right time. This is a key driver of predictive marketing journeys. We have received a patent on our unique personalization approach and are recognized by the leading analyst from Gartner as a Cool Vendor in AI Marketing.
• Data management: Data sits at the core of our product. We invest billions of user, product and behavior stream every day in real-time into our data/delta lake. We perform ETL on the TBs of data to create schema-less user-product interaction graphs to compute product recommendations and predictive scores.
• Analytics and Experimentation: Experimentation and optimization are critical to the evaluation, iteration, and adoption of AI workflows. We have developed sophisticated ETL workflows and adopted analytics stack to measure the ROI of AI and help marketers make data-driven decisions.
• Cloud-native Infrastructure: Framework to provision big data cloud infrastructure in a reproducible, version controlled, elastic and automated manner. Helps us scale our cluster easily. Also makes it easy to upgrade existing clusters or bring new clusters to play with the latest open source releases. We have provisioned our production Hadoop, Spark, Kafka, and Druid clusters using this framework.
• Open source: We love open source, our entire data infrastructure, and data science stack is built on open source. Hadoop, Hive, Hbase, S3, Kafka, Spark, Airflow, Druid, scikit/pytorch, H2O.ai, Docker, and Redis forms our infrastructure and application stack.
• Whitepapers/Courses: We are pioneers in bringing practical AI to the marketing industry. We have developed AI courses and whitepapers to educate marketers and adopt AI in their marketing workflow.

Responsibilities

• You will work on full-stack data science components and applications such as ETL pipelines, recommendations, predictive targeting, auto-optimization
• You will own, design, and develop data infrastructure and applications to power cutting, edge AI algorithms over petabytes of data using offline/online data integration
• You will build data products for growth and product marketers, think AWS services like AutoML for marketers
• You will work with experienced technical and product teams with proven entrepreneurial success
• You will have the opportunity to hire, mentor, and lead the team.

Requirements

• At least 5 years of industry experience in software development, including significant experience deploying ML algorithms to production environments
• Proven experience with distributed systems like Spark, Kafka, HDFS, Cassandra, Hive and HBase.
• BS/Masters/PhD in Computer Science or related engineering disciplines
• Strong architecture, algorithmic design and familiarity with open source AI/ML tools.
• A real passion for thinking from first principles and building from ground up
• Experience building a production ML systems would be a plus