Machine Learning Engineer

Role overview Join an AI/ML team building the intelligence layer behind a personalized health platform. The work spans classical pattern recognition on biometric signals to natural language capabilities powering conversational health agents.

Responsibilities - Develop, train, and deploy ML models for health prediction and personalization use cases - Fine-tune large language models for health-domain conversational experiences - Build evaluation frameworks and ongoing monitoring for model performance and drift - Translate product and clinical requirements into practical ML solutions alongside product partners - Prototype novel approaches to health AI and assess their viability - Optimize models for inference latency and cost efficiency at production scale

Requirements - 4+ years of applied ML engineering experience - Strong Python programming paired with PyTorch or TensorFlow - Practical experience with LLMs including fine-tuning, retrieval-augmented generation, and prompt engineering - Solid grounding in statistics and core ML fundamentals - Track record of deploying and maintaining models in production environments - Clear communication skills for working across engineering, product, and clinical stakeholders

Nice to have - Experience working with health or biomedical datasets - Publications at recognized ML or AI conferences - Background in time series forecasting - Familiarity with recommendation system design

Benefits and work setup - Competitive base salary of $200,000–$300,000 plus equity - Premium health, dental, and vision insurance - Unlimited PTO and flexible hours - Remote-first culture with optional San Francisco office access - $5,000 annual learning and development budget - Family access to a product subscription benefit