At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
We are hiring a Post-Doctoral Researcher for our AI Research team. This 24 month fixed-term position is designed for recent PhD graduates looking to deepen their research experience on challenging problems at the frontier of AI — specifically, applying machine learning to high-impact real-world domains like medicine, finance, and law.
You'll collaborate closely with Snowflake researchers, scientists, and engineers on fundamental and applied problems, publishing high-quality work while helping shape how AI integrates with the world's most consequential industries.
Collaborate with research mentors to formulate research projects or novel applications of machine learning aligned with the team's mission, with a focus on AI applied to medicine, finance, or law
Conduct independent and collaborative research and publish high-quality work at top AI and domain-applied research venues
Design and execute large-scale experiments using modern deep learning frameworks, writing high-quality, reusable code
Develop models and systems that bridge AI capabilities with real-world application requirements in high-stakes, regulated domains
Engage across teams — including with domain experts and applied engineering — to ground research in practical constraints and real-world impact
Contribute to the broader research community through publications, open-source releases, and collaboration with academic and industry partners
PhD (or expected completion by start date) in Computer Science, Statistics, Mathematics, or a related STEM field, or equivalent practical experience
Research experience in machine learning or AI techniques (e.g., open-source projects, campus lab experience, research internships, or publications)
Proficiency in Python and experience training deep learning models using PyTorch, JAX, TensorFlow, or equivalent frameworks
One or more scientific publication submissions in top AI or applied domain research venues (e.g., NeurIPS, ICML, ICLR, AAAI, ACL — or equivalent high-quality venues in medicine, finance, or law)
Ability to work independently and collaborate effectively across research teams and domain experts
Research background at the intersection of AI and one or more of: medicine (clinical NLP, medical imaging, drug discovery), finance (quantitative modeling, risk, forecasting, market analysis), or law (legal NLP, contract analysis, reasoning, compliance)
Experience designing, fine-tuning, or evaluating LLMs or foundation models in applied domain settings
Familiarity with evaluation challenges in high-stakes AI — fairness, explainability, robustness, or regulatory constraints
Publications at domain-applied AI venues (e.g., CHIL, ML4H, FinNLP, NLLP)
Experience with retrieval-augmented generation (RAG), knowledge graphs, or structured reasoning over domain-specific data
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
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