Responsibilities

• Define and drive the multi-year vision and roadmap for ML platform and infrastructure supporting personalization, discovery, content intelligence, and emerging GenAI experiences
• Develop and own the data platform strategy, delivering clean, curated datasets that encode business logic and provide science teams with trusted, model-ready data foundations
• Build end-to-end ML tooling and pipelines that enable ML builders to discover datasets, ideate modeling approaches, conduct research and experimentation, and seamlessly productionize models from prototype to production
• Support large-scale model training, real-time inference, and compute optimization across CPU and GPU to ensure models perform efficiently at production scale
• Define and evolve the feature store strategy, supporting both online and offline data serving while minimizing online/offline skew to ensure consistency between training and serving environments
• Own the developer experience for ML builders by delivering self-service tools, reusable components, and standardized workflows that increase productivity, reduce operational overhead, and improve cost efficiency, scalability, and availability
• Enhance the measurement platform to monitor model performance in production, track input and output metric alignment, and ensure models deliver intended business outcomes
• Influence senior leadership and cross-functional stakeholders to align on platform strategy, investment priorities, and trade-offs
• Drive adoption of platform capabilities across teams by ensuring solutions are intuitive, reliable, and measurably better than existing workflows

Requirements

• 7+ years of end to end product delivery experience
• 4+ years of technical product or program management experience
• Bachelor's degree
• Experience with feature delivery and tradeoffs of a product
• Experience owning/driving roadmap strategy and definition
• Experience leading engineering discussions around technology decisions and strategy related to a product
• 3+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
• Deep understanding of MLOps, model training, evaluation metrics and data pipelines

Preferred

• Experience in project management methodologies, business analysis, or process improvement
• Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
• Familiarity with recommendation systems is a bonus
• Fluency in technology alternatives with ability to weigh pros and cons of different technical approaches

Benefits

• comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave