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As a Research Intern at Snorkel AI, you’ll contribute to internal research and academic collaborations—helping 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.
Job Responsibility:
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 teams—reading papers, proposing hypotheses, and iterating quickly
Requirements:
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