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 |
|---|---|---|
| Software Engineer 5 – Agent Platform, AI Platform Software Engineer 5 role focused on building and operating the Agent Platform infrastructure at Netflix, including the Agent SDK, MCP Gateway, and evaluation stack. The role involves enabling other engineers to build, deploy, and run production-grade AI agents, with a strong emphasis on the full agent lifecycle (plan/act/observe, tool integration, deployment, operations) and robust evaluation mechanisms. | AgentEval Gate | 9 |
| Senior Machine Learning Manager, Merchandising and Content Understanding Senior Manager leading a team of Research Scientists, ML Engineers, Data Scientists, and Analytics Engineers focused on Multimodal Large Language Models (MLLMs) and agentic systems for deep, complex content understanding. The role involves defining strategy, overseeing end-to-end initiatives, managing and growing a multidisciplinary organization, and establishing best practices for complex algorithmic and agentic systems at Netflix scale. |
| AgentPost-train |
| 9 |
| Senior ML Engineer, GenAI - Games Senior ML Engineer at Netflix Games focusing on integrating GenAI into game development, including gameplay mechanics, asset generation, NPC behaviors, and internal tools. The role involves optimizing model performance, bridging research and production, and mentoring junior engineers. Requires strong software engineering skills in C++/C# and experience with the ML lifecycle. | AgentServe | 8 |
| Senior Game Engineer, GenAI - Games Senior Game Engineer at Netflix focused on integrating Generative AI into gameplay systems to create dynamic and player-responsive experiences. The role involves working with game designers, implementing GenAI features, integrating them into core game systems, developing safety and quality guardrails, and using GenAI for rapid iteration and tool building. Requires strong game engineering experience and applied GenAI skills with LLMs or Diffusion models. | Agent | 8 |
| AI Engineer 6 - AI Foundation & Tooling, Ads Platform Staff AI Engineer to build AI infrastructure and agentic workflows for software development lifecycle at Netflix Ads Platform. This greenfield role focuses on applied AI, leveraging LLMs, agentic frameworks, and RAG to solve infrastructure and product problems, aiming for AI-native engineering. | Agent | 8 |
| Machine Learning Scientist 5 - Ads Forecasting Netflix is seeking a Machine Learning Scientist to build predictive models for their ad-supported tier. This role involves developing supervised ML models to forecast campaign delivery outcomes, replacing a simulation engine with learnable models. The scientist will own the end-to-end modeling process, from feature engineering to production deployment and monitoring, collaborating with ML engineers and cross-functional partners. The goal is to create accurate, robust, and explainable forecasts to power various aspects of the ad business. | Agent | 7 |
| Machine Learning Scientist 5 - Sales, Ads DSE Machine Learning Scientist role focused on building AI agents and automation systems to improve sales productivity and revenue growth within Netflix Ads. The role involves defining the ML roadmap, designing and deploying production ML models and AI agents end-to-end, and partnering with analytics engineers and stakeholders. | Agent | 7 |
| Storyboard Artist - Ink Netflix is seeking a Storyboard Artist to join their Inkubator team, focusing on developing animated shorts and specials using experimental GenAI-native production pipelines. The role involves creating high-quality storyboards, exploring hybrid workflows with traditional and new tools, and contributing to feature-quality content. The artist will collaborate with creative leadership, translate scripts into visuals, brainstorm story elements, and drive look development by blending generative imagery with traditional methods. Building workflows, templates, and scripts is also a key responsibility, alongside ensuring timely delivery and fostering a collaborative environment. | Agent | 7 |
| Senior Manager, Critical Operations & Reliability Engineering Senior Manager of Site Reliability Engineering to lead infrastructure organizations at Netflix, focusing on setting reliability standards and leading the SRE team supporting the streaming architecture. The role involves managing an evolving infrastructure towards a millions-of-agents ecosystem, with AI agents embedded in incident management, capacity planning, and reliability posture. Requires experience in AIOps, anomaly detection, or agentic infrastructure systems, and driving technical adoption across complex organizations. | AgentEval Gate | 7 |
| Manager, Member Experience - Ads DSE Manager for Netflix's Member Experience team within Ads Data Science and Engineering. This role focuses on understanding and optimizing the impact of ad delivery policies on member experience using causal inference and predictive models. The team will build models and workflows to drive ad delivery optimization, balancing revenue, member experience, and advertiser outcomes. The role involves leading a team of ML Scientists, Data Scientists, and Analytics Engineers, fostering partnerships, and ensuring high-quality technical outputs. | Agent | 7 |
| Machine Learning Scientist 5, Markeplace - Ads DSE Machine Learning Scientist at Netflix focused on building and optimizing the ad tech ecosystem. This role involves designing and implementing ML algorithms for ad quality and performance, training and evaluating models on large-scale production data, and developing evaluation frameworks. The goal is to create data-driven solutions for relevant ad experiences and advertiser results, balancing member experience and revenue. | AgentEval Gate | 7 |
| Engineering Manager, Ads Signals & Targeting Engineering Manager for Netflix Ads, focusing on core targeting and signals platforms. This role involves leading teams to build and scale systems for audience and contextual targeting, enabling relevant and privacy-forward ad experiences. It requires partnering with ML teams on advanced models, working on high-scale, low-latency services, and shaping signal activation for targeting, optimization, and measurement. The role emphasizes ownership, rapid execution, and building high-performing teams in a fast-paced environment. | AgentData | 7 |
| Manager, Generative Workflows - Production Technology Manager role focused on translating GenAI experimentation into production-ready guidance for content production partners at Netflix. This involves consulting on feasibility and value, identifying where GenAI improves quality/efficiency/speed, and grounding the technology in creative and operational constraints. The role will prototype, deliver, optimize workflows, educate teams, and provide feedback to product and innovation teams. | Agent | 7 |
| Trust Services and Enforcement Engineering Manager Engineering Manager for Netflix's Trust Services and Enforcement team, focusing on building and scaling fraud mitigation services. This role involves applying Generative AI to enhance detection and counter evolving AI-driven attack vectors, while managing a team and driving cross-functional alignment on security risk posture. | Agent | 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 |