Machine Learning Scientist 5 - Games

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. Data Science and Engineering (‘DSE’) at Netflix is aimed at using data, analytics, causal inference, machine learning (ML), and sciences to improve various aspects of our business. The AI initiative at Netflix Games is dedicated to pioneering the next generation of interactive entertainment. We have the ambition to transform how players interact with stories, characters, and worlds by empowering gameplay experience with AI. We work at the intersection of creative game design and cutting-edge machine learning, ensuring that dynamic storytelling is not only novel but also coherent, immersive, and safe for our players. We are seeking an experienced L5 ML Scientist specialized in forecasting and audience research . In this role, you will: Build Foundational ML Building Blocks: Develop sophisticated embeddings and models that incorporate deep game-specific signals to solve high-impact business problems, including audience insights, opportunity sizing, and forecasting. Accelerate Product Development: Build the tools, models, and pipelines required to accelerate DSE workflows across games portfolio, studios, product, and platform. Bridge the Netflix Ecosystem: 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. Design Scalable Pipelines: Create end-to-end ML pipelines that accelerate and enable DSE members across games to uncover actionable insights and build data-intensive game features. Elevate ML Practices: Establish the technical standards for how ML capabilities are applied across game domains. Who Will Succeed in This Role: 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 You can digest the latest research paper in the morning and ship a functional prototype or foundational model by the afternoon. You can bridge the gap between technical ML architecture and business objectives, translating product needs into rigorous technical specifications. You thrive in zero-to-one environments, enjoying the freedom to choose your stack and define the engineering standards for a new domain. You have a foundational understanding of causal inference principles, allowing you to discern when a predictive model is sufficient vs. when a causal approach is required. You have a passion for developing reusable ML capabilities to unlock and accelerate development work broadly. Nice to Have: Experience working with game development teams, particularly in game design and engineering. Experience with building production-grade ML systems, including MLOps best practices. Have strong engineering skills, particularly in designing and optimizing evaluation frameworks (e.g., Python, PyTorch, LangChain). Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is . This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employ ... (truncated, view full listing at source)