Senior Engineering Manager, Machine Learning

Role overview Lead a machine learning team developing and improving models used to assess e-commerce transactions and manage risk. This is a hands-on player-coach role: you will guide people and technical direction while helping the team evaluate uncertain ideas, strengthen production systems, and balance near-term improvements with longer-range research.

Responsibilities - Coach and develop engineers through regular feedback, career planning, goal setting, and support with technical and interpersonal growth. - Build a healthy, collaborative team across locations; address conflicts, identify capability gaps, and contribute to hiring and interview training. - Work with technical leads to assess proposals, clarify hypotheses, and decide which experiments merit time and resources, which need another iteration, and which should stop. - Stay close to code, evaluation pipelines, and statistical evidence so you can help distinguish reliable production results from findings that may not generalize. - Connect model performance and experimental outcomes to business impact, and communicate tradeoffs and decisions clearly to risk leadership. - Set a high bar for reproducibility, correctness, and reliability while making room for experimentation and learning from unsuccessful results.

Requirements - 8+ years in machine learning, data science, or adjacent software engineering, including at least 3 years managing people and supporting their development. - Deep expertise in either engineering or applied statistics, with practical working competence in the other. - Experience leading work where outcomes are uncertain, setting direction, changing course when evidence shifts, and keeping the team aligned through those changes. - Strong written and spoken communication, including the ability to explain technical measures in terms of business outcomes. - Sound independent judgment about priorities and impact in a fast-moving environment with limited supervision. - Commitment to high-quality work that is correct, reproducible, and dependable.

Benefits and work setup The role is described as remote. US benefits include flexible paid time off, retirement matching, stock options, performance-based bonus eligibility, parental leave, health and related insurance coverage, therapy support, and a learning budget. US base salary is listed by location tier at $200,000–$245,000 annually; the role may also include a performance bonus and stock options.