Summer Intern - Machine Learning Engineer

Job Description

The Role

Applied Machine Learning Research at Netflix improves various aspects of our business, including personalization algorithms, content generation, system optimization, and innovative tooling for artists. Our research spans many areas of machine learning, including recommender systems, reinforcement learning, computer vision, natural language processing, optimization, and operations research. Great applied research also requires robust machine learning infrastructure, another large area of emphasis at Netflix.

Applicants are encouraged to express their interest in one or multiple types of internships listed if your skills and qualifications are aligned.

We are looking for individuals with the following qualifications:
• Currently enrolled PhD student in the Machine Learning or adjacent Engineering space.
• Some experience with the following machine learning areas:
• Foundational science: Practical experience in supervised and/or unsupervised machine learning or data science methods.
• 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.
• Experience programming in Python.
• Curious, self-motivated, and excited about solving open-ended challenges at Netflix.
• Great communication skills, both oral and written.
• Comfortable with software engineering best practices (e.g. version control, testing, code review, etc.).

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).
• In the Airtable form, you will be asked to select a primary (or secondary) ML area for your potential internship. This will be used to map your application to particular teams & projects.
• You will be asked to include a short (max one page) statement describing your research experiences and interests, and (optionally) their relevance to Netflix Research. For inspiration, have a look at the Netflix research site.

Internships at Netflix

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 a few fixed start dates in May or June 2025 to accommodate varying school calendars. Conditions permitting, our 2025 summer internships will be located in our Los Gatos, CA office, or in our Los Angeles, CA office, depending on the team.

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 - $110/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.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity of thought and background 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.

Jobcode: Reference SBJ-d9pb39-3-15-2-239-42 in your application.