Netflix

Product Manager for AI Video at Netflix, focusing on capabilities from pitch to post-production. Drives AI/ML product strategy, translating creative needs into technical requirements and collaborating with R&D and engineering to deploy AI models for video production.

Technical Director for GenAI in the Games organization at Netflix, responsible for driving the engineering strategy, leading teams, developing AI-native gameplay mechanics, and scaling core GenAI capabilities like model inference and fine-tuning pipelines for player experiences.

Research Engineer at Netflix to apply ML expertise to design, develop, and scale personalization systems and algorithms for member experiences. This role involves creating production-ready ML solutions, optimizing models, and conducting experiments to improve key business metrics.

Machine Learning Scientist role focused on pricing science within a B2C subscription business. The role involves designing and implementing causal inference approaches and ML models to understand the impact of pricing actions on member behavior, conducting elasticity and willingness-to-pay research, and evolving measurement tools. The scientist will partner with Finance & Strategy and Product teams to translate findings into actionable business recommendations and own work from ideation to production systems.

Machine Learning Scientist role focused on ad ranking and personalization at Netflix, involving designing, implementing, and evaluating ML models and optimization algorithms on large-scale production data. The role requires strong collaboration with product teams and communication of technical results to stakeholders.

Head of Technology for a GenAI-native animation studio, responsible for the end-to-end technology stack including artist tools, production workflows, infrastructure, security, and data platforms. This role involves defining technology strategy, leading engineering teams, enabling creative ambition through AI, and scaling operations for multiple productions. Key areas include generative workflows, asset management, inference/training technologies, data pipelines for model fine-tuning, and secure AI usage.

Engineering Manager for Netflix's Search & Voice Systems team, focusing on LLM advancements for content discovery and personalization. The role involves leading a team of engineers, developing roadmaps, and driving innovation in high-traffic distributed systems for search and recommendation experiences.

Director of Product role at Netflix focused on scaling content understanding systems using AI/ML. The role involves driving product strategy, leading product managers and functional teams (operations, ratings, analysts, editorial) to automate and scale areas like ratings, content analysis, and catalog management. It requires experience with ML/AI solutions, shipping AI-powered products, and understanding of computer vision methods.

Netflix is seeking a Senior Manager for the Ads Forecasting team. This role will lead a team responsible for building and owning scalable forecasting platforms and models for ad supply, demand, and revenue. The team also develops simulators for campaign setup and ad delivery optimization. The ideal candidate will have deep domain expertise in ad forecasting and simulation, experience leading science/ML teams, and the ability to translate business objectives into analytical solutions.

Product Manager role at Netflix focused on integrating AI/ML into content platform operations and publishing tools to create personalized experiences, automate asset creation, and optimize content distribution. Requires experience with the ML lifecycle, launching AI-enabled products, and evaluating ML techniques.

Product Manager role at Netflix focused on integrating AI/ML into content platform operations and publishing tools to create personalized experiences and optimize content promotion, localization, and distribution. The role involves building strategic roadmaps, leading incubation of new AI capabilities, and translating AI advancements into scalable products.

Machine Learning Scientist to develop, optimize, and deploy scalable ML solutions for content strategy, acquisition, scheduling, and advertising at Netflix. The role involves end-to-end ML model development, from ideation to deployment and monitoring, with a focus on informing content decisions and partnering with cross-functional teams.

Software Engineer for AI for Member Systems at Netflix, focusing on designing, developing, and scaling machine learning algorithms that power the Netflix experience. This role involves collaborating with researchers and product managers to improve personalization systems, enable offline experiments, and drive the implementation of scalable, production-ready solutions for algorithms. The engineer will also contribute to better software engineering practices and systems.