The L5 ML Scientist role at Netflix focuses on leveraging machine learning to enhance audience insights and forecasting within the gaming sector. The Data Science and Engineering team aims to merge creativity with advanced technology to transform player interactions with stories and characters. This position requires a strong background in ML and the ability to bridge technical architecture with business objectives. The ideal candidate will thrive in a dynamic environment, contributing to innovative game design and development.

• Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
• 5+ years of experience leading complex, end-to-end ML projects that impact end-customer experiences.
• 3+ years of experience navigating large-scale technical organizations to align roadmap priorities and share infrastructure.
• A foundational understanding of causal inference principles.

• Develop sophisticated embeddings and models that incorporate deep game-specific signals to solve high-impact business problems.
• Build the tools, models, and pipelines required to accelerate DSE workflows across games portfolio, studios, product, and platform.
• Act as a key liaison with the broader Netflix DSE and AI teams to adopt, adapt, and tailor global Netflix capabilities for the unique requirements of the gaming space.
• Create end-to-end ML pipelines that accelerate and enable DSE members across games to uncover actionable insights.
• Establish the technical standards for how ML capabilities are applied across game domains.

• Employees at Netflix are often offered flexible, people-first benefits—unlimited time away, generous parental leave, global family-forming support, mental-health programs (mindfulness, free counseling/coaching), and health coverage tailored by country. Financially, Netflix pays at personal top-of-market and lets employees choose their mix of cash vs. fully-vested 10-year stock options, alongside donation and volunteer matching. Convenience perks can include trust-based travel/expense policies, relocation support, and “Work, Not Drive” rideshare flexibility.