About the role#
Netflix is looking for PhD students to join us for a Winter 2027 internship in Los Gatos. This program embeds you directly into our teams to work on open-ended machine learning challenges. You will contribute to projects that improve our personalization algorithms, creative tooling, and understanding of our member base and content library. This is a paid, full-time, onsite position for a minimum of 12 weeks.
What you'll do#
- Conduct research in areas like recommender systems, reinforcement learning, computer vision, and natural language processing.
- Build and maintain the machine learning infrastructure required to support your research.
- Develop and deploy pipelines for training or production environments.
- Collaborate with internal teams to solve complex, open-ended technical problems.
What you'll need#
- Currently enrolled in a PhD program, preferably in your 2nd to 4th year.
- Pursuing a degree in Computer Science, Mathematics, Statistics, Data Science, Computer Engineering, Economics, Biology, or Physics.
- Proficiency in at least one programming language, such as Python, Java, Scala, or C/C++.
- Familiarity with machine learning frameworks like PyTorch, TensorFlow, or JAX.
- You must be returning to school for at least one semester or quarter following the internship.
Location & details#
- This role is based onsite at our headquarters in Los Gatos, California.
- You must be available to work 40 hours per week.
- The internship term begins in early January 2027.
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.
