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. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.
We are looking for Machine Learning Engineers to help design, build, and deploy machine learning models and systems that power personalized recommendations, content optimization, search, streaming quality, and other data-driven features across the Netflix platform. We are looking for candidates who will develop and maintain scalable ML pipelines and infrastructure, collaborate with data scientists, product managers, and engineers to translate business needs into ML solutions, and experiment with new algorithms and techniques to improve user experience and operational efficiency.
Candidates will be evaluated to find the best fit in one of our organizations, including Content, Choosing & Conversation, Commerce or AI for Member Systems. You can find a detailed list of teams across these organizations to learn more. Applicants are encouraged to express their interest in one or multiple types of teams/ domain areas listed if your skills and qualifications are aligned.
We are looking for individuals with the following qualifications:Currently enrolled student pursuing an advanced degree (Master’s or PhD) in areas such as Computer Science, Machine Learning, Artificial Intelligence, Computer Engineering, Mathematics, Statistics, Data Science, Computational Biology, Chemistry, Physics, Cognitive Science or a related field
Some experience with the following machine learning areas:
Foundational science: Practical experience in supervised and/or unsupervised machine learning, data science methods, ML operations, and possibly experience in Large Language Models or Reinforcement Learning.
Software engineering: Comfortable with software engineering best practices (e.g. version control, testing, code review, etc.).
End-to-end systems: Familiarity end-to-end machine learning pipelines (e.g. training or production deployment) and common challenges like explainability.
Practical experience with programming and machine learning, evidenced by projects, classwork, or research.
Proficiency or familiarity with languages such as Python, Java, Scala, or Spark
Experience with ML frameworks and libraries such as Pandas, NumPy, or Scikit-learn
Curious, self-motivated, and excited about solving open-ended challenges at Netflix.
Comfortable with software engineering best practices (e.g. version control, testing, code review, etc.).
Great communication skills, both oral and written.
Intent to return to your degree-program after the completion of the internship.
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.
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 for the summer. 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 choice of fixed start dates in January 2026 (Winter), May or June 2026 (Summer) to accommodate varying school calendars. Our summer internships will be located at our headquarters in Los Gatos, CA, with limited opportunities in Los Angeles or New York depending on the team.
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.
Job is open for no less than 7 days and will be removed when the position is filled.
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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.