Senior Engineering Manager, Machine Learning

What you bring

• 10+ years building software and machine learning or AI systems, with a clear progression in scope and impact.
• 3+ years managing ML or software engineers, including hiring and developing senior and staff-level technical leaders.
• A strong software-engineering foundation and a record of shipping ML systems that run in production.
• Technical depth across the ML lifecycle: data and labeling, experimentation, model selection, deployment, APIs, CI/CD, observability, evaluation, retraining, and incident response.
• Sound judgment across classical ML, deep learning, LLMs, rules, and conventional software.
• Experience setting direction for NLP, classification, extraction, entity resolution, risk, fraud, recommendation, or similarly complex applied-ML domains.
• Fluency with modern LLM systems, including structured outputs, tool use, agent orchestration, retrieval, evaluation, latency, quality, and cost trade-offs.
• A record of translating an ambiguous business problem into a sharp roadmap, measurable outcomes, and shipped systems.
• Strong people leadership. You create leverage through clear ownership, candid feedback, delegation, and coaching.
• Executive-level communication and cross-functional influence. You can make a hard technical trade-off legible to senior leaders and leave the room with a decision.
• You use modern AI tools to move faster, verify their output, and can spot plausible-looking work that should not ship.
• An A-player mindset with a strong bias for action: you raise the bar, move with urgency, stay resilient through ambiguity, and take ownership to deliver meaningful outcomes.
• Nice to have
• Built ML infrastructure or MLOps platforms used by multiple teams.
• Document intelligence, OCR, graph systems, identity resolution, trust and safety, fraud, or risk.
• Operated ML in a compliance-sensitive domain such as fintech, legal tech, HR tech, healthcare, or security.
• Python, AWS/SageMaker or similar cloud ML platforms, Snowflake, Spark, and modern data tooling.
• Launched a new AI product from early customer discovery through production scale.
• #LI-TD1
• Pay Transparency Disclosure
• We use geographic cost of labor as an input to develop ranges for our roles and as such, each location where we hire may have a different range. If this role is remote, we have listed the top to the bottom of the possible range, but we will specify the target range for an exact location when you are selected for a recruiting discussion. For more information on our compensation philosophy, see our website.