Netflix is offering a paid 12-week AI and machine learning infrastructure internship for PhD students in 2027, with compensation typically ranging from $40 to $85 per hour.
Netflix has opened applications for its Machine Learning/AI Infrastructure Engineering Intern (AI Platform) PhD, Winter 2027 opportunity in Los Gatos, California.
The paid internship is designed for current PhD students working in areas such as computer science, distributed systems, networking, machine learning and computer engineering. The program provides an opportunity to work on AI infrastructure supporting Netflix’s machine learning systems.
Applications are reviewed on a rolling basis, and the position may close once filled.
Opportunity Overview
| Detail | Information |
|---|---|
| Organization | Netflix |
| Opportunity | AI Infrastructure Engineering PhD Internship |
| Start | January 2027 |
| Duration | Minimum 12 weeks |
| Location | Los Gatos, California |
| Work type | Onsite; remote candidates may be considered |
| Study level | PhD |
| Field | AI, Machine Learning, Computer Science, Systems |
| Compensation | Typically $40–$85 per hour |
| Application | Rolling basis |
| Requisition | JR42220 |
What the Netflix Internship Involves
The AI Platform team builds infrastructure supporting Netflix’s machine learning and AI systems.
Interns may work around areas including:
- Distributed systems and distributed training
- ML training platforms
- Post-training and offline infrastructure
- GPU-optimized inference
- Model-system co-design
- Machine learning infrastructure
- Large-scale computing and serving systems
The internship is intended for researchers who enjoy working at the intersection of systems and machine learning rather than focusing solely on model development.
Who Can Apply?
Applicants should currently be pursuing a PhD in a relevant field such as:
- Computer Science
- Distributed Systems
- Systems
- Networking
- Machine Learning
- Computer Engineering
- A related discipline
Applicants should also have research or applied experience in relevant AI infrastructure or systems areas.
Strong Python skills are required, while experience with Go, C++ or Rust is an advantage. Familiarity with technologies such as Ray, Kubernetes, Spark and ML training or serving stacks can also strengthen an application.
Publications or research aligned with systems or applied machine learning venues are listed as a nice-to-have.
Internship Compensation
Netflix states that its internship market range is typically $40 to $85 per hour.
The company explains that actual compensation can vary according to factors including the specific role, skills, experience and location.
The internship is paid and has a minimum duration of 12 weeks.
Important Program Details
The internship begins in January 2027 and is designed for students who will return to school for at least one semester or quarter after completing the internship.
Netflix says that conversion or return offers depend on business needs and available headcount and are not guaranteed.
The company also describes its internship program as a personalized experience where interns are matched with projects and teams according to their interests and skills.
How to Apply
Applicants should submit their application through the official Netflix careers platform.
After applying, candidates will receive an Airtable form that must also be completed. Netflix states that an application will not be considered complete until this form has been submitted.
The application should include:
- Resume or CV
- Complete contact information
- Relevant coursework
- Publications, where applicable
- A short statement describing research experience and interests
Applications are reviewed on a rolling basis, so applicants are encouraged to apply early.
Official Application
Apply for the Netflix AI Infrastructure Engineering PhD Internship
Application Tips
Because this is a specialized PhD opportunity, applicants should make their technical and research experience easy to identify.
Consider highlighting:
- Relevant distributed systems or ML infrastructure research.
- Technical projects involving GPUs, model serving or distributed computing.
- Python and systems programming experience.
- Relevant publications and research contributions.
- Experience with technologies such as Kubernetes, Ray or Spark.
- A concise explanation of why your research interests align with AI infrastructure.
How Competitive Is This Opportunity?
Opportunities Feed assessment: This is a specialized opportunity with a narrow academic and technical eligibility profile. Applicants need current PhD enrollment and relevant research or applied experience in AI infrastructure, systems or related areas.
Netflix does not publish an acceptance rate in the information provided, so no application success percentage should be assumed.
Application Deadline
There is no fixed closing date stated in the posting.
Netflix says applications are reviewed on a rolling basis and that the application window will remain open until the roles are filled. The position is also stated to be open for at least seven days and may be removed when filled.
Frequently Asked Questions
Is the Netflix AI internship paid?
Yes. Netflix states that internships are paid, with a typical internship market range of $40–$85 per hour.
Who is eligible for this internship?
The opportunity is aimed at current PhD students in fields such as computer science, systems, networking, machine learning and computer engineering.
When does the internship start?
The internship has a January 2027 start date.
How long is the internship?
The minimum internship duration is 12 weeks.
Can international students apply?
The provided posting does not give a general nationality restriction. Applicants should review the official posting and application requirements concerning work authorization and location.
Is the internship remote?
The role is listed as onsite in Los Gatos, California, but the posting says remote candidates may be considered for this team.
Is a return job guaranteed?
No. Netflix states that conversion or return offers depend on business needs and headcount and are not guaranteed.
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