Netflix is reinventing entertainment from end to end. We are revolutionizing how shows and movies are produced, pushing technological boundaries to efficiently deliver streaming video at massive scale over the internet, and continuously improving the personalization of how entertainment is presented to our more than 200 million members around the globe.
Applied Machine Learning Research at Netflix improves various aspects of our business, including personalization algorithms, search, systems optimization, content valuation, tooling for artists, and streaming video optimization. As such, our research spans many Machine Learning areas, including recommender systems, causal inference, reinforcement learning, computer vision, computer graphics, natural language processing, optimization, operations research and systems. Great applied research also requires great Machine Learning infrastructure, another large area of emphasis at Netflix.
In 2022, Netflix Research will be hosting a small number of summer Machine Learning internships. We will be looking for both Machine Learning research internships, as well Machine Learning engineering & infrastructure internships.
We will only consider candidates that are legally authorized to work in the USA. We are looking for individuals with the following qualifications:
- Currently enrolled PhD or MS student in the Machine Learning space.
- Experience with at least one of the following ML areas: Personalization & Recommender Systems; Computer Vision, Graphics, Natural Language Understanding & Multimodal ML; Search & Conversational AI; Fairness, Accountability & Transparency; Causal Inference & Modeling; Reinforcement Learning & Bandits; ML for Systems, Productivity & Operations; or ML Platform & Infrastructure
- Experience programming in at least one language (e.g. Python, Scala, Java or C/C++).
- Curious, self-motivated, and excited about solving open-ended challenges at Netflix.
- Great communication skills, both oral and written.
Nice to have:
- Past publications in relevant conferences or journals.
- Comfortable with distributed computing environments such as Spark or Presto.
- Comfortable with software engineering best practices (e.g. version control, testing, code review, etc.)
In order 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 exactly one 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.
The Summer Internship
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 to accommodate varying school calendars. Conditions permitting, our 2022 summer internships will be located either remotely, in our Los Gatos, CA office, or in our Los Angeles, CA office, depending on the team.
Netflix is an equal opportunity employer that celebrates 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, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.