Staff Machine Learning Engineer, Consumer Risk AI

What you'll do

• Architect and build shared streaming and batch feature pipelines, data infrastructure, and model training and evaluation frameworks.
• Own real-time model serving and integration with the decision engine, meeting sub-second latency requirements.
• Set ML engineering standards, automate model lifecycle workflows, and guide engineers and cross-team partners.

What they ask for

• BS, MS, or PhD in Computer Science, Engineering, or a related quantitative field, or equivalent practical experience.
• 8+ years building production software, substantial experience with ML systems, and prior experience leading an engineering effort across teams.
• Proficiency in Python and SQL; production experience with Spark, Flink, or equivalent for streaming and batch processing.
• Experience owning a multi-team data or ML platform and deploying models to real-time production serving under hard latency budgets.

Nice to have

• Risk, fraud, payments, or credit experience, ideally in real-time decisioning.
• Feature platform, entity resolution, rules engine, regulated data, or AI agent orchestration experience.

Pay

Mountain View USD $202,500 - $274,000 base salary

Tools

Python, SQL, Spark, Flink, AWS, SageMaker

AI focus

Builds and operates ML infrastructure and real-time models for fraud, account takeover, and other consumer risk decisions; also develops agent-assisted engineering and automated model lifecycle workflows.