Staff Machine Learning Engineer, Homefeed

Role overview Provide senior technical leadership for machine learning systems that improve recommendation research and retrieval. The work focuses on building agents that can propose and investigate ideas, implement changes, run experiments, and learn from outcomes, alongside contributions to generative retrieval methods. This is an individual contributor role spanning applied research, production engineering, and collaboration across technical teams.

Responsibilities - Own a major area of automated recommendation research and coordinate its direction with technical leads and partner teams. - Build language-model agents that connect hypothesis generation, implementation, experiment execution, evaluation, and learning from prior results. - Design rigorous evaluations of agent behavior and research outcomes, then use results to improve reliability and efficiency. - Develop generative retrieval approaches, including structured content representations, and integrate them into production recommendation systems. - Move promising ideas from prototypes through offline and online experiments to production launches. - Integrate work with machine learning infrastructure, making informed tradeoffs among model quality, iteration speed, compute cost, and operational complexity. - Raise engineering quality through implementation, reviews, documentation, and mentorship.

Requirements - Degree in computer science, machine learning, or a related field, or equivalent practical experience. - At least 8 years building and shipping machine learning or AI systems, with substantial hands-on engineering and technical leadership. - Demonstrated experience building agentic systems for complex tasks and evaluating and improving their performance. - Strong machine learning foundations and depth in areas such as applied language models, representation learning, recommendations, retrieval, or ML systems. - Experience taking research into reliable production systems and assessing impact through meaningful experiments. - Strong software design, implementation, technical review, cross-team collaboration, and communication skills. - A record of leading a substantial technical area and mentoring engineers; careful verification of AI-generated code and analysis.

Benefits and work setup The position can be based anywhere in the country and requires in-person collaboration about one to two times per quarter. Relocation support is not available. Compensation includes base pay and equity; the listed US base range is $189,308–$389,753.