Staff Applied Machine Learning Engineer, Intelligent Data, Signals & Systems

What you'll do

• Build production ML systems that transform customer behavior and product context into trusted signals for ranking and recommendations.
• Design data and signal contracts defining usage, freshness, provenance, confidence, and calibration for downstream consumers.
• Manage end-to-end lifecycles for search, retrieval, propensity, and next-best-action systems from feature generation to monitoring.
• Evaluate business impacts including trust, fairness, risk, compliance, and long-term engagement beyond short-term conversion metrics.
• Translate ambiguous goals from cross-functional partners into measurable machine learning system designs.
• Utilize AI and agents to accelerate development, testing, documentation, and the creation of reusable capabilities.

What we're looking for

• You must have 12+ years of experience building and operating production software and ML systems for business-critical products.
• You must possess deep expertise in intelligent systems such as ranking, retrieval, recommendations, search, and personalization.
• You must demonstrate strong production ML judgment regarding feature pipelines, model serving, experimentation, monitoring, and feedback loops.
• You must be able to evaluate impact beyond short-term conversion, including trust, fairness, risk, and compliance.
• You must have experience using AI-assisted engineering tools with appropriate verification and testing for customer-impacting systems.
• You should have experience with semantic retrieval, embeddings, two-tower models, or LLM-powered decision systems.
• You should have experience with experimentation techniques like multi-objective optimization or counterfactual evaluation.
• You should have experience building reusable feature platforms, decision services, and model-derived data products.