Lead Machine Learning Engineer

Build next-generation personalization for Disney+ and Hulu by leading the ideation, development, iteration, and productionization of recommendation algorithms. This onsite role in San Francisco, CA supports a team that blends applied ML science with end-to-end engineering to improve recommendations using modern AI and LLM techniques, backed by rigorous offline and online evaluation.

What you’ll do

• Ideate, develop, iterate on, and productionize personalization algorithms across the recommendation stack, including core ranking, content and user understanding models and graphs, candidate retrieval, and post-ranking systems.
• Apply modern AI and LLM techniques to recommendation systems, including generating and improving recommendations, strengthening evaluation, and accelerating model build and improvement cycles.
• Shape recommendation approaches by contributing ideas on evaluation methodology and helping define model data, features, and objectives; support other scientists in taking ideas from concept to production.
• Drive the technical vision and innovation agenda for personalization by identifying high-impact opportunities and influencing how the team approaches them.
• Design and run rigorous offline and online experiments, and help improve evaluation systems and methodology over time.
• Collaborate closely within the team and across Engineering, Product, and Data, communicating methodologies clearly to both technical and non-technical audiences and managing stakeholder expectations.
• Build production-worthy, maintainable systems with strong development, testing, and deployment standards, and provide support when production issues arise.

Core requirements

• 7+ years of experience developing machine learning models and deploying them to production systems.
• Strong background in applied ML science, end-to-end ML engineering, ideally with experience in recommendation systems modeling.
• Hands-on experience with AI and LLM techniques and an understanding of the modern AI landscape.
• Proficiency with PyTorch, TensorFlow, Databricks, Spark, and SQL.
• In-depth understanding of modern machine learning methods, models, and their mathematical foundations.
• Strong written and verbal communication skills.
• Collaborative, personable working style, thriving across teams rather than operating in isolation.

Bonus and benefits

• Bonus and/or long-term incentive units may be provided as part of the compensation package.
• Full range of medical, financial, and/or other benefits depending on level and position offered.

Additional qualifications (preferred)

• PhD in computer science, statistics, math, or a related quantitative field.
• Publications or papers in machine learning or AI, especially in recommender systems.
• Production experience developing content recommendation algorithms at scale.
• Experience with reinforcement learning or related sequential decision-making approaches.
• Experience with recommendation system evaluation methodology, including offline evaluation and A/B experimentation.

Education: BS or MS in Computer Science, Engineering, or a related field.

Salary range: USD 187,900 to 252,000 per year.

Technologies: PyTorch, TensorFlow, Databricks, Spark, SQL, AI, LLM.