Netflix has 86 active AI-related job listings. The majority of these roles are focused on agents, comprising 34% of the total, and application development, at 33%. Engineering is the primary function for these positions. The company is actively hiring for roles involving model serving, fine-tuning, and recommender systems. Over the last 30 days, Netflix has added 22 new AI roles, representing a 16% increase compared to the previous 30-day period.
Currently tracking 53 active AI roles, down 44% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $131k–$1500k (avg $606k).
Netflix currently has 80 active AI-related roles in our index. The most common open titles are: AI Engineer 6 - AI Foundation & Tooling, Ads Platform, AI Product Manager, Content Platform Operations & Publishing, AI/ML Scientist Intern, AIMS AI Foundations (PhD) – Fall 2026, Analytics Engineer 5 - Ad Ranking, Art Director - Ink. Most positions are in Engineering and Research.
Netflix's active AI hiring is concentrated in: agents (36%), application (24%), serving infrastructure (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Netflix is hiring AI talent in: United States (76 roles), Poland (4 roles), Canada (3 roles).
Job postings at Netflix most frequently mention: Machine Learning, Ads & Ranking ML, Production ML Systems, Generative AI, Data Science.
In the past 30 days, Netflix has posted 12 new AI-related roles. That is a -33% change versus the prior 30 days (18 → 12).
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Scientist 5 - Ad Ranking 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. | ShipEval Gate | 7 |
| Manager, Data Science & Engineering - Title & Launch Management Manager for a Data Science and Engineering team at Netflix, focusing on building automated systems and AI/agentic solutions for content launch and promotion. The role involves leading a multidisciplinary team, shaping strategy, and driving execution of end-to-end AI solutions. | Agent |
| 7 |
| Head of Technology - Ink 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. | ShipData | 7 |
| Software Engineer 5 - Inkubator Software Engineer to build enterprise-wide technology and platforms for an AI-native production environment for animated shorts and specials. The role involves evaluating AI developments, packaging workflows, prototyping, and developing tools for artists and technical directors to support scalable GenAI-native production. | Agent | 7 |
| Technical Director - Inkubator Netflix is seeking Technical Directors for its Inkubator team to create animated shorts and specials using experimental, creative-led, GenAI-native production pipelines. The role involves supporting show-specific workflows, strategizing with artists to develop creative solutions, providing tool support, documenting training materials, and beta testing new tools. A key responsibility is identifying and performing custom fine-tuning for models based on show requirements, integrating both internal and external tooling. The role also involves monitoring artist pain points, troubleshooting data handoffs, evaluating new tool releases, identifying standardization opportunities, and collaborating on compute and workstation requirements. | Post-trainServe | 7 |
| Machine Learning Engineer (L4/L5) - Emerging Game Technologies Machine Learning Engineer focused on MLOps, deployment, and performance optimization for AI-driven game concepts, bridging research and production for cloud and edge environments. | Serve | 7 |
| Engineering Manager - Search & Voice Systems 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. | Ship | 7 |
| Creative Evaluation Lead, Artwork Netflix is seeking a Creative Evaluation Lead, Artwork to bridge creative, product, and technical teams to transform promotional artwork workflows using AI. This role involves contributing to AI R&D, evaluating AI model outputs, executing AI solutions for content launches, building learning loops, translating creative needs into AI opportunities, leading training, and staying updated on AI advancements in imagery. The ideal candidate has extensive creative making experience, familiarity with AI image tools, and experience with QC processes for artwork assets. | Eval GatePost-train | 7 |
| Machine Learning Engineer 5 - Ads Inventory Management & Forecasting Machine Learning Engineer at Netflix focused on Ads Inventory Management & Forecasting. The role involves building end-to-end ML model deployment and inference infrastructure for low-latency real-time ad systems, handling large data volumes with Spark, and productionizing predictive models for campaign effectiveness forecasting. It also includes building scalable simulation solutions for inventory scenarios and collaborating with cross-functional teams. | ServeData | 7 |
| Director of Product, Catalog and Content Understanding, Content Platform Operations & Publishing 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. | Ship | 7 |
| Senior Manager, Ads Forecasting DSE 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. | Ship | 7 |
| Engineering Manager, Core Applications - AI for Member Systems Engineering Manager for Core Applications AI team at Netflix, focusing on building foundational AI capabilities for member systems, including reward models, entity libraries, LLM post-training frameworks, and utility optimization. The role involves leading a team, setting vision, designing APIs, and partnering with other teams to ensure adoption and integration of shared components. | Post-trainAgent | 7 |
| AI Product Manager, Content Platform Operations & Publishing 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. | Ship | 7 |
| AI Product Manager, Content Platform Operations and Publishing 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. | Ship | 7 |
| Research Scientist 5, Identity - Ads DSE Research Scientist role focused on identity modeling for Netflix's ad-tier members, involving machine learning, statistics, and data analysis techniques. The role requires experience in identity graphs, privacy, differential privacy, and anonymization to improve advertiser performance and member experience. Responsibilities include applying ML to business problems, identifying research opportunities, diagnosing data/model assumptions, delivering documented outputs, and serving as a strategic partner to stakeholders. | Data | 7 |
| Machine Learning Scientist (L4) - Content & Conversation Modeling 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. | Ship | 7 |
| Machine Learning Engineer 5 - Ads Platform Engineering Netflix is hiring Machine Learning Engineers for their Ads Platform Engineering teams. The role involves building and deploying ML models for low-latency real-time ad systems, focusing on areas like inventory forecasting, ad serving, programmatic interfaces, member experience, and audience targeting. Responsibilities include developing and productionizing predictive models for campaign effectiveness, yield optimization, bid ranking, and dynamic allocation, as well as building scalable simulation solutions. Experience with big data tools like Spark and proficiency in languages like Java, C++, Python, or Scala are required. | ServeAgent | 7 |
| Software Engineer L4/L5, Model Serving Systems, Machine Learning Platform Netflix is seeking a Software Engineer for their Machine Learning Platform team to develop and expand their model serving systems, focusing on infrastructure for LLMs and other large foundation models. The role involves building scalable, robust systems for online ML model inference, optimizing for latency and cost, and ensuring high availability and performance. This is a highly cross-functional role partnering with various engineering and data science teams. | ServeAgent | 7 |
| Software Engineer L4/L5 Training Platform, Machine Learning Platform Software Engineer on the Machine Learning Platform (MLP) team, responsible for designing and building the platform that powers large-scale machine learning model training, fine-tuning, model transformation, and evaluations workflows for the entire company. Focuses on optimizing systems and models for scale and cost-effectiveness, and designing user-friendly APIs for ML practitioners. | DataPost-train | 7 |
| Software Engineer 4/5– AI for Member Systems 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. | ShipServe | 7 |
