Sr. Applied AI/ML Engineer

Description Vi manages a petabyte scale data lakehouse that drives data and ML pipelines across all our products. Vi is looking for an engineer with deep expertise building and scaling big-data and ML pipelines. The role will be a hybrid between an FDE that owns integrations of customer data with Vi’s data lakehouse and a platform engineer responsible for packaging Vi’s products into repeatable, scalable, automated pipelines. Tech Stack - Apache PySpark, Apache Iceberg, AWS EMR, Glue, S3 - Python, PyTorch, sklearn, xgboost, catboost, mlflow - AWS SageMaker, Airflow Key Responsibilities - Own the design and implementation of data and ML pipelines based on a combination of customer first party data and Vi’s internal data lakehouse. - Prototype predictive insight products and run rapid feasibility studies to assess new commercial opportunities for Vi’s capabilities built on petabyte scale data lakehouse. - Identify commonalities between customer engagements to synthesize reusable data capabilities. What We’re Looking For - Deep expertise building large-scale data analytics pipelines with Apache Spark. - Comfortable using Python and AWS technologies for data engineering and ML. - Strong communication skills to interact with technical counterparts across customer accounts to coordinate data integrations. Nice to Have - Experience in the healthcare and life sciences domain. - Familiarity with ML and statistical modeling methodologies and experimental design. Originally posted on Himalayas