AI/ML Scientist Intern, AIMS AI Foundations (PhD) – Fall 2026

Netflix•Los Gatos, CA

4d•$40 - $85•Hybrid

About The Position

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. 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. 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.

Requirements

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 Haves

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)