About the role#
The AI Platform team builds the infrastructure that runs Netflix machine learning and AI systems. We focus on large-scale training platforms, offline infrastructure, and GPU-optimized inference and serving. This role is for PhD researchers who enjoy working at the intersection of systems and machine learning. You will work closely with modeling teams on model-system codesign to solve open-ended infrastructure challenges.
What you'll do#
- Build infrastructure for training platforms and GPU-optimized inference.
- Engage in model-system codesign by collaborating with modeling teams.
- Solve complex infrastructure challenges at the scale of Netflix.
What you'll need#
- Current enrollment in a PhD program for Computer Science, Computer Engineering, Distributed Systems, Networking, or a related field.
- Research or applied experience in distributed systems, distributed training/serving, ML training platforms, or GPU-optimized inference.
- Proficiency in Python and experience with systems languages such as Go, C++, or Rust.
- Familiarity with distributed compute frameworks like Ray, Kubernetes, or Spark.
- You must be returning to school for at least one semester or quarter after the internship concludes.
Location & details#
- This is a paid, full-time internship starting in early January 2027.
- The internship lasts for a minimum of 12 weeks.
- The role is based at our headquarters in Los Gatos, California, though remote candidates are considered.
About Netflix
Netflix provides entertainment services including television series, films, games, and live programming. The company operates across various genres and languages for a global audience. Founded in 1997, it maintains headquarters in Los Gatos, California. The organization employs over 18,000 people and functions as a public company.
How to get in at Netflix
Securing an internship at Netflix requires speed because roles often receive high volumes of interest. Intern Insider sends an instant alert the moment a role matching your target is published anywhere, so you apply among the first. Early applicants get seen before the pile grows, which helps your profile stand out during the initial review. Beyond timing, networking plays a role in the hiring process. Intern Insider surfaces the recruiters behind the company's roles so you can reach out directly to ask about the role or a referral. Engaging with the right people materially improves response rates compared to submitting a cold application.
