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Vi operates a petabyte-scale data lakehouse powering data and ML pipelines across its product suite. This Senior Applied AI/ML Engineer role bridges data engineering and platform engineering, combining responsibilities for integrating customer data with Vi's lakehouse infrastructure and packaging products into repeatable, scalable automated pipelines.
You will own the design and implementation of data and ML pipelines leveraging both customer first-party data and Vi's internal data lakehouse. Key responsibilities include prototyping predictive insight products, running rapid feasibility studies to assess new commercial opportunities, and identifying commonalities across customer engagements to synthesize reusable data capabilities.
The technical stack includes Apache PySpark, Apache Iceberg, AWS EMR, Glue, and S3 for data engineering; Python, PyTorch, scikit-learn, XGBoost, and CatBoost for ML; and AWS SageMaker and Airflow for orchestration and deployment.
Required qualifications: deep expertise building large-scale data analytics pipelines with Apache Spark; proficiency in Python and AWS technologies for data engineering and ML; strong communication skills to coordinate data integrations with technical counterparts across customer accounts.
Nice-to-have: experience in healthcare and life sciences domains; familiarity with ML and statistical modeling methodologies and experimental design.
This is a high-impact role for an engineer who thrives at the intersection of data infrastructure, machine learning, and customer-facing problem-solving at scale.
