AI Researcher Summer Intern
3 weeks ago
AI Researcher Summer Intern At Snorkel, we believe meaningful AI doesn't start with the model, it starts with the data. We're on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world's largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler About the Internship As a Research Intern at Snorkel AI, you'll contribute to internal research and academic collaborationshelping explore and validate new ideas that may shape future publications, open-source artifacts, and long-term product directions. This is a research-first role, designed for interns who want to do deep technical work with real-world relevance. You'll work closely with Snorkel researchers on open-ended projects and produce clear research outputs (experiments, prototypes, internal writeups, and potentially publications depending on project fit and timing). What You'll Do Develop and evaluate new methods for data development for foundation models and enterprise AI systems (e.g., dataset construction, augmentation, synthetic data, and evaluation). Research supervision and evaluation techniques such as rubrics and verifiable rewards. Design experiments and run rigorous empirical studies (ablations, benchmarks, error analysis). Build lightweight research prototypes and tooling in Python to support internal studies. Collaborate with academic partners and internal research teamsreading papers, proposing hypotheses, and iterating quickly. Example Project Areas Synthetic data generation + filtering for specialized tasks Evaluation datasets and benchmarks for LLM / RAG / agent behavior Data-centric methods for improving reliability, calibration, and failure-mode coverage Evaluating HITL data annotation processes, gaps, and improvements What We're Looking For Current student in a PhD in ML/AI/CS. Strong ML fundamentals and demonstrated research ability (papers, preprints, or substantial research artifacts). Excellent Python skills and experience with modern ML tooling (PyTorch, NumPy, etc.). Ability to operate in ambiguous, research-driven problem spaces with strong experimentation habits. Clear communication: can write concise technical notes and present findings. Nice to have Prior work on evaluation, data curation, synthetic data, weak supervision, NLP, or multimodal ML. Experience collaborating with academic labs or participating in research programs. Internship Details Duration: Summer (flexible start/end) Location: Hybrid (Redwood City/SF) or Remote (US) Compensation: Competitive, commensurate with experience Why Snorkel Research Work with a research org advancing data-centric AI and foundation-model development, in close partnership with labs and enterprises. Join a company with deep research roots and a substantial body of peer-reviewed work in this space. Get mentorship and ownership on projects that can influence long-term research direction.
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