Job Description
📋 Description Define the technical strategy for ML models and infra across search and recommendations. Architect and ship high-leverage models and systems in production. 🎯 Requirements 8+ years in ML/data science or related field. Deep Python expertise and ML frameworks (scikit-learn, PyTorch, TensorFlow). Experience in recommendations, personalization, NLP, or explainable AI. Deep familiarity with ML lifecycle (experiment tracking, monitoring, feature pipelines) at scale. Ability to architect and scale ML infrastructure (embedding retrieval, ranking, GNNs) in production. Experience leading/mentoring engineers and driving roadmap alignment. 🎁 Benefits Ownership: Equity in a fast-growing company Financial Wellness: 401(k) match, competitive compensation, financial coaching Family Support: Paid parental leave, fertility benefits, parental coaching Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend Growth: $2,000 learning stipend, ongoing development Remote & Office: Internet, commuting, and free lunch/gym in SF office
