Machine Learning/AI Infrastructure Engineering Intern (AI Platform) PhD, Winter 2027

Posted 9 Hours Ago
Be an Early Applicant
Los Gatos, CA, USA
In-Office
40-85 Hourly
Internship
News + Entertainment
The Role
Build and optimize infrastructure for Netflix’s machine learning and AI systems, including distributed training, offline and post-training platforms, GPU-optimized inference, and serving. Collaborate with modeling teams on model-system codesign and solve large-scale infrastructure challenges. The internship lasts at least 12 weeks and is intended for PhD students returning to school afterward.
Summary Generated by Built In

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

Netflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages.

The AI Platform team builds the infrastructure that Netflix's ML and AI systems run on, from large-scale training platforms and post-training/offline infrastructure to GPU-optimized inference and serving. 

You'll work on infrastructure that's closely co-designed with modeling teams (model–system codesign), so this role suits PhD researchers who enjoy working at the intersection of systems and ML rather than pure modeling.

We are looking for individuals with the following qualifications:

  • Currently enrolled student pursuing a PhD in Computer Science, Distributed Systems, Systems, Networking, Machine Learning, Computer Engineering, or a related field

  • Research or applied experience in one or more of the following:

    • Distributed systems, distributed training/serving infrastructure

    • ML training platforms, post-training or offline infrastructure

    • Inference and serving optimization, GPU-optimized inference

    • Model–system codesign

  • Proficiency in Python; experience with systems languages (Go, C++, or Rust) is a strong plus

  • Familiarity with distributed compute frameworks (e.g., Ray, Kubernetes, Spark) and ML training/serving stacks

  • Curious, self-motivated, and excited about solving open-ended infrastructure challenges at Netflix scale

  • Strong written and verbal communication skills

Nice to have:

  • Publications or strong research alignment with systems-track venues (OSDI, SOSP, NSDI) or applied ML venues

  • Prior industry or internship experience in ML infrastructure

Program details:

  • 12-week minimum internship with a start date early January 2027 

  • Based at our Los Gatos, CA headquarters, may be open to remote candidates 

  • Intended for students returning to school for at least one semester/quarter after the internship; conversion/return offers are based on business need and headcount, and are not guaranteed

For your application to be considered complete:

  • You will be sent an Airtable form shortly after you submit your application on our careers site; your application will not be considered complete until you fill out and submit this form.

  • Include a Resume or CV with complete contact information (email, phone, mailing address) and a list of relevant coursework and publications (if applicable). You will be asked to include a short statement describing your research experiences and interests, and (optionally) their relevance to Netflix Research. For inspiration, have a look at the Netflix Research site.

  • Applications will be reviewed on a rolling basis and it's in the applicant's best interest to apply early. The application window will remain open until roles are filled.

About the Internship Program

At Netflix, we offer a personalized experience for interns, and our aim is to offer an experience that mimics what it is like to actually work here. We match qualified interns with projects and groups based on interests and skill sets, and fully embed interns within those groups. Netflix is a unique place to work and we live by our values, so it's worth learning more about our culture.

  • Internships are paid and are a minimum of 12 weeks, with a fixed start date the second week of January 2027 (Winter). Location is flexible for this team, with remote candidates considered.

  • This program is intended for students who will be returning to school for at least one semester/quarter following the internship to be eligible for full time employment. Conversion or return offers are based on business need and headcount, and are not guaranteed.

At Netflix, we carefully consider a wide range of compensation factors to determine the Intern top of market. We rely on market indicators to determine compensation and consider your specific job, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location. The overall market range for Netflix Internships is typically $40/hour - $85/hour.

This market range is based on total compensation (vs. only base salary), which is in line with our compensation philosophy. Netflix is a unique culture and environment. Learn more here.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Apply now and help us shape the future of entertainment at Netflix!


Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Job is open for no less than 7 days and will be removed when the position is filled.

Skills Required

  • Currently enrolled in a PhD program in Computer Science, Distributed Systems, Systems, Networking, Machine Learning, Computer Engineering, or a related field
  • Research or applied experience in distributed systems, distributed training or serving infrastructure, ML training platforms, post-training or offline infrastructure, inference and serving optimization, GPU-optimized inference, or model-system codesign
  • Proficiency in Python
  • Familiarity with distributed compute frameworks such as Ray, Kubernetes, or Spark, and ML training or serving stacks
  • Strong written and verbal communication skills
  • Curiosity, self-motivation, and enthusiasm for solving open-ended infrastructure challenges
  • Experience with systems languages such as Go, C++, or Rust
  • Publications or strong research alignment with systems-track or applied ML venues
  • Prior industry or internship experience in ML infrastructure
  • Must be returning to school for at least one semester or quarter after the internship

Netflix Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Netflix and has not been reviewed or approved by Netflix.

  • Fair & Transparent Compensation Compensation is positioned as “personal top of market” with regular recalibration and broad posted ranges for senior roles that signal the philosophy. The cash‑forward structure and clearly described pay‑mix choices help set expectations on how pay is determined.
  • Equity Value & Accessibility Employees can choose the mix of cash versus fully vested 10‑year stock options, with grants structured to be retained even after departure. This employee‑directed design increases accessibility and control over equity participation.
  • Healthcare Strength Health coverage is described as comprehensive across medical, dental, vision, and mental health, with employer funding designed to offset premiums. Additional resources like counseling/coaching and wellness support reinforce breadth in care access.

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The Company
HQ: Los Gatos, CA
13,212 Employees
Year Founded: 1997

What We Do

Netflix is the world's leading streaming entertainment service with 209 million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.

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