AI Applied Scientist, Code Intelligence

Snowflake • Menlo Park, CA

51d

About The Position

Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level. Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level. We’re seeking an AI Applied Scientist to drive Code Intelligence at Snowflake. Your mission: build AI-powered capabilities that supercharge developer efficiency and elevate developer experience for both Snowflake engineers and our customer developers. You’ll turn cutting-edge ideas into dependable tools—shipping systems that make coding, reviewing, and testing faster, safer, and more delightful at scale.

Requirements

• MS or PhD in Computer Science (or related field).
• Strong Python skills and fluency with a commonly used ML stack (e.g., PyTorch and XGBoost or similar).
• Hands-on experience building ML data pipelines, plus a habit of rigorous evaluation and experiment design.
• Familiarity with serving stacks and vector stores; comfort learning what you don’t know.
• Eagerness to learn build systems and CI/CD. Previous experience with build systems and CI/CD is a plus but not required.

Nice To Haves

• LLMs for code, program analysis/ASTs, retrieval/RAG, prompt engineering & eval, large-scale A/B testing, backend/service development, and familiarity with OLAP systems like Snowflake.

Responsibilities

• Build AI features that move the needle on developer outcomes—accelerating PR cycle time and time-to-first-commit, reducing review latency and defects, improving test coverage, and raising developer satisfaction.
• Design and deliver systems in three focus areas: automated testing, code review assistance, and coding agents that integrate with repos and workflows.
• Prototype quickly and iterate, then productionize and harden solutions for reliability, performance, and safety, with a strong bias toward shipping impact.
• Develop end-to-end ML pipelines: data preparation, training/fine-tuning, evaluation, and online serving—including experiment design, telemetry, and A/B measurement.
• Collaborate closely with Engineering Systems (our developer productivity team) to integrate into build, test, and deployment workflows.
• Write clear, maintainable Python and work across the stack to design, implement, and debug components from modeling to services and evaluation harnesses.
• Contribute to a culture of high-quality engineering: code health, documentation, and grounded decision-making informed by data.
• Write technical blogs and research papers to share your findings.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees