Staff Research Scientist, AI Agents & LLMs
Snowflake is hiring a Staff Research Scientist, AI Agents & LLMs for a remote role open to applicants in United States. It pays $236k-$339k a year and Level rates it ; you can apply on Snowflake.
Level's read on this job
- Builds AI ●●●● is how Level rates this research scientist role: the job is building AI systems.
- The listed pay starts 24% above the typical research scientist posting on Level.
- The posting lists this role as remote.
- Tools and skills the posting cites include AI agents, fine tuning and AI research.
- Level lists 354 other open roles at Snowflake.
AI in this role
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.
THE MISSION
We are seeking a Staff Research Scientist to serve as a technical pillar within our AI research organization. You will not just execute on roadmaps—you will define them.
At the intersection of autonomous agents and large language models (LLMs), you will build the models and systems that turn enterprise data into self-directed, decision-making agents—shifting from passive data access to autonomous execution.
Our team operates at the frontier of enterprise AI, delivering both state-of-the-art models and production systems, including:
Arctic LLM: Enterprise foundation models optimized for performance and efficiency
Arctic-Text2SQL: Post-trained reasoning models with frontier-level quality at a fraction of cost and latency
Snowflake Intelligence: Brought research to production through agentic innovations in multi-step reasoning, Deep Research for structured and unstructured insights, and system optimization
Arctic Inference: High-performance LLM serving stack (Shift Parallelism, SwiftKV), open-sourced and powering Snowflake Cortex
Arctic Long-Context Training: Enables 1M+ token context training on a single H200 GPU
Agent World Models (AWM): RL training across 1,000+ synthetic environments for tool-using agents
We focus on core challenges such as reliable reasoning, long-horizon planning, grounded generation, and scalable model and agent development.
IN THIS ROLE, YOU WILL:
Define research direction in Agentic AI and LLMs
Develop models: train, fine-tune, and align models for enterprise reasoning and tool use
Advance autonomous agents: drive state-of-the-art capabilities in multi-step reasoning and tool use
Advance the stack: retrieval, grounding, memory, and multi-agent coordination
Establish evaluation standards for reliability, safety, and efficiency
Drive research breakthroughs into production within Snowflake’s platform
Mentor and lead to amplify the team’s technical impact
Contribute to the field through publications and open source
WE’RE LOOKING FOR:
Ph.D. in Computer Science or a related field with a strong publication record
Expertise in LLM development (training, fine-tuning, alignment, or post-training)
Experience with agentic systems (multi-agent systems, tool use, or agent optimization)
Strong systems thinking under real-world constraints (latency, cost, reliability)
Proven technical leadership and end-to-end ownership
Ability to translate research into impactful systems
WHY SNOWFLAKE?
Frontier AI, Full Stack
Work across the full stack—from foundation models (Arctic LLM, Arctic Text2SQL) to agent systems (Snowflake Intelligence) and inference/training infrastructure (Arctic Inference, Arctic Training).
State-of-the-Art, Real Impact
Drive cutting-edge research that ships—powered by massive enterprise data and production workloads.
Hard, Meaningful Problems
Build autonomous systems for reliable reasoning over enterprise data—where correctness, cost, and latency all matter.
Open Research Culture
Publish, open-source, and help shape the field.
Snowflake is growing fast, and we are scaling our team to accelerate AI innovation.
Are you ready to build the brain for the Enterprise Data Cloud?
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.
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
How we rate this
Staff Research Scientist, AI Agents & LLMs at Snowflake rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in research scientist jobs at this level
Pay
- This job starts at
- $236k
- Typical research scientist job
- $191k
This posting starts 24% above the typical research scientist job. See research scientist jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Tell me about a research question you investigated. What did you find?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI agents, Fine-tuning, and AI Research. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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