Currently tracking 53 active AI roles, down 44% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $131k–$1500k (avg $606k).
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.
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 |
|---|---|---|
| Video Algorithms Intern, Video Coding (Gaussian Splatting), Fall 2026 Internship role focused on exploring and improving Gaussian Splatting (GS) for future streaming formats, involving research into model compression, training time reduction, and rendering efficiency. | Data | 7 |
| Machine Learning Scientist 5 - Games Machine Learning Scientist 5 focused on forecasting and audience research within Netflix Games. The role involves building foundational ML building blocks like embeddings and models, accelerating product development through tools and pipelines, bridging the Netflix ecosystem, designing scalable ML pipelines, and establishing technical standards for ML application in game domains. Requires a PhD and significant experience in leading end-to-end ML projects and navigating large technical organizations. | Data |
| 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 |