Staff Machine Learning Engineer

Role overview Staff-level machine learning engineer owning personalization across consumer surfaces that serve recommendations, search, and feed experiences. The role blends hands-on modeling with architectural direction, setting the multi-year roadmap for how custom representations and ranking systems evolve across a family-focused product.

Responsibilities - Drive fuzzy business problems from initial sketch through production model, staying accountable for real customer outcomes - Build custom embeddings from raw data that go beyond off-the-shelf image and text models, and own them as multiple surfaces adopt them - Make the modeling and architecture decisions that span teams and are costly to reverse - Run the full ML lifecycle including orchestration, deployment, monitoring, and the retraining loop that keeps models honest - Set the standard for how personalization uses AI, including the evaluations that catch confidently wrong models before they ship - Partner as a peer with product, design, and data to shape what gets built - Coach senior engineers through ambiguous and technically hard calls

Requirements - Several years of experience shipping production machine learning, with strong opinions held loosely - Track record of building recommender systems or personalization that reached real users at scale, with measurable impact - Deep fluency in the Python ML ecosystem including pandas, scikit-learn, XGBoost, and PyTorch - Comfort across the full lifecycle from orchestration through monitoring, not only training - Demonstrated ability to build custom representations from raw data rather than defaulting to generic embeddings - A zero-to-one mindset that defines problem spaces and owns end-to-end delivery

Benefits and work setup - Remote-first across the US and Canada, with the whole company gathering in person twice a year - Small pods of three to five engineers so work stays visible and scope stays wide - Company-paid medical with fully covered dental and vision, 401(k) match, generous paid parental leave for birthing and non-birthing parents, a gradual return-to-work program, a paid company-wide week off at year end, a remote-work stipend, and mental-health and wellness support