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. Members can play, pause, and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.
The AIMS AI Foundations team sits within the AI for Member Systems (AIMS) organization and focuses on the research and engineering foundations that underpin next-generation member experiences. Our work spans agentic AI systems, LLM evaluation frameworks, multimodal modeling and training data curation. We work at the intersection of applied research and product impact, translating novel ideas into measurable improvements for Netflix members worldwide.
We are seeking a PhD intern to join us for a Fall 2026 engagement (targeting a September 2026 start, with flexibility). This is a hands-on applied research role: you will be expected to design and run experiments, build prototypes, and contribute meaningfully to ongoing team projects in one or more of our core domain areas.
Domain Areas
Interns will be matched to projects within one or more of the following focus areas:
- Agentic AI – Developing and evaluating systems that reason, plan, and act autonomously, including tool use, retrieval-augmented reasoning, memory and goal management, and feedback-driven learning.
- LLM Evaluations – Designing rigorous evaluation frameworks, benchmarks, and quality metrics to assess language model behavior, reliability, and alignment.
- Multimodal Data – Building models and pipelines that integrate text, image, video, audio, and other data modalities; experience with large vision-language models and modality fusion.
- LLM Training Data Curation – Researching and implementing methods for selecting, filtering, and improving training data quality to enhance model performance.
Qualifications
Must Have
- Currently enrolled PhD student in Computer Science, Machine Learning, Artificial Intelligence, Computer Engineering, Mathematics, Statistics, Data Science, Cognitive Science, or a related field
- Able to work 40 hours per week during the fall/winter
- Proficiency in Python
- Strong foundation in machine learning, deep learning, and algorithms/statistics
- Experience with one or more major ML frameworks: PyTorch, TensorFlow, or JAX
- Ability to design, run, and interpret ML experiments in an applied research setting
- Ability to translate research ideas into practical prototypes and evaluations
- Strong oral and written communication skills for presenting technical work clearly
Nice to Have
- Coursework or research experience in advanced NLP, advanced ML systems, or reinforcement learning
- Familiarity with HuggingFace, Transformers, Pandas, NumPy, and scikit-learn
- Publications in top venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, AAAI, CIKM, WWW, UAI, CVPR, or related
- Experience with agentic systems, multimodal modeling, or applied LLM workflows
- Exposure to evaluation design, benchmarking, and model quality tradeoffs
- Familiarity with distributed computing environments such as Spark or Presto
- Comfortable with software engineering best practices (version control, testing, code review)
About the Internship
At Netflix, we offer a personalized experience for interns. Our aim is to provide an experience that mirrors what it is truly like to work here. Interns are fully embedded within their team, own meaningful projects, and operate with the same autonomy as full-time employees.
- Internship duration: minimum 12 weeks, targeting a September 2026 start date
- Location: Los Gatos, CA headquarters or remote; flexible depending on team
- This program is intended for students who will be returning to school for at least one semester/quarter following the internship
For Your Application to Be Considered Complete
- Submit your application on our Netflix Careers site
- Complete the Airtable supplemental form sent after initial application submission — applications are not considered complete without it
- Include a resume or CV with complete contact information, relevant coursework, and publications (if applicable)
- Include a short statement describing your research experience and interests, and optionally their relevance to the AIMS AI Foundations team’s focus areas
- Applications are reviewed on a rolling basis. For inspiration, visit the Netflix Research site.
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.
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.