Senior Engineering Manager - Machine Learning Data Enablement

What you'll do

• Build and lead teams responsible for data integration, data quality, metadata, and ML-critical data infrastructure for training and inference.
• Set technical strategy and improve data quality, monitoring, ownership, and SLAs across the data lifecycle.
• Standardize third-party data onboarding and improve discovery and use of internal data.

What they ask for

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (or its equivalent) and 8 years of engineering experience, including at least 3 years of direct people management experience.
• Owned production data pipelines for both offline training and online inference.
• Experience building and scaling data systems in modern stacks and distributed systems architecture.
• Experience leading complex cross-functional initiatives and designing and enforcing production data quality and observability frameworks.

Nice to have

• 10+ years in data engineering and ML platform or ML data platform roles, with 5+ years managing engineering teams.
• Experience with feature stores and real-time feature delivery or equivalent feature transformation interfaces used in inference.

Pay

$195,000—$270,000 USD (base salary)

Tools

Databricks/Spark, Python, SQL, AWS, Kubernetes, Terraform, CI/CD

AI focus

Leads infrastructure and processes that enable ML teams to discover, evaluate, trust, and productionize data for model training and inference.