Principal / Staff Applied Research Scientist

Reposted 7 Days Ago
Be an Early Applicant
Menlo Park, CA, USA
In-Office
236K-339K Annually
Senior level
Artificial Intelligence • Big Data • Cloud • Machine Learning • Software • Database • Analytics
Let's build a world where data and AI turn possibilities into reality.
The Role
Lead applied research combining formal methods, automated reasoning, and modern ML/LLMs to build verified, trustworthy data infrastructure; prototype and ship production features, partner with engineering and product, and scale methods across teams.
Summary Generated by Built In

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.

Snowflake's Data Engineering organization builds the platform that ingests, transforms, and stores data for modern lakehouse architectures — powering billions of queries, DML, and DDL operations with industry-leading price-performance. We lead the industry's shift to open data lakes through our work on Iceberg and Polaris, and we deliver capabilities like Snowpark, Dynamic Tables, cross-region replication, time travel, and zero-copy cloning at enterprise scale.

We are investing in a new line of applied research — building toward verified data infrastructure and trustworthy data systems — that brings formal methods, automated reasoning, and modern AI techniques to bear on the hardest problems in our distributed systems and developer tooling. The goal is to improve correctness, reliability, and engineering velocity at a scale very few platforms operate at. We're hiring at both the Staff and Principal level; we'll calibrate the offer to the candidate's experience and scope of impact.

What you'll do
  • Lead research projects that apply formal methods, program analysis, automated reasoning, and AI-driven techniques (including code generation and modeling) to real problems in our cloud data platform.

  • Translate research ideas into prototypes, then into shipped capabilities that move concrete business metrics — quality, velocity, reliability, and operational performance at scale.

  • Partner closely with engineering leaders, product managers, and key customers to identify high-leverage opportunities and turn them into deliverables.

  • Influence the engineering and product roadmap; advise leaders on which research directions are pragmatic and which are not.

  • Train and uplevel engineering teams on new methods, and scale those methods across the organization.

  • Maintain expertise at the frontier of the field through publications, conference participation, open-source contributions, and patent filings.

What we're looking for
  • PhD (or equivalent research experience) in Computer Science or a closely related field.

  • Depth across the areas this role sits at the intersection of:

    • Formal methods — e.g., model checking, theorem proving, SAT/SMT, program verification, type systems, or program analysis.

    • Distributed systems — designing, reasoning about, or verifying large-scale concurrent and distributed systems.

    • Software engineering — strong fundamentals; able to go from a research idea to production-quality code in collaboration with engineering teams.

    • AI / ML — practical experience applying modern ML, including LLMs, to systems problems such as code generation, synthesis, or automated reasoning.

  • 8+ years applying theoretical computer science to large-scale software systems — ideally cloud data platforms, distributed systems, or developer infrastructure.

  • Demonstrated ability to drive company-level initiatives in partnership with engineering and product leadership. (Weighted more heavily for Principal-level candidates.)

  • Track record of technical contribution to the field — publications, open-source work, patents, or comparable evidence of impact.

  • Comfortable in a fast-paced, ambiguous environment where impact is measured by what ships.

About working here

Every Snowflake employee is expected to follow the company's confidentiality and security standards for handling sensitive data, and to keep customer information secure and confidential as an essential part of their duties.

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

Skills Required

  • PhD or equivalent research experience in Computer Science or closely related field
  • 8+ years applying theoretical computer science to large-scale software systems (cloud data platforms, distributed systems, or developer infrastructure)
  • Depth in formal methods (model checking, theorem proving, SAT/SMT, program verification, type systems, or program analysis)
  • Expertise in distributed systems design, reasoning about concurrency, and verifying large-scale systems
  • Strong software engineering skills; able to translate research into production-quality code
  • Practical experience applying modern ML/LLMs to systems problems such as code generation, synthesis, or automated reasoning
  • Track record of technical contributions: publications, open-source work, patents, or comparable impact
  • Demonstrated ability to drive company-level initiatives in partnership with engineering and product leadership
  • Comfortable working in a fast-paced, ambiguous environment focused on shipping impact

Snowflake Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Snowflake and has not been reviewed or approved by Snowflake.

  • Fair & Transparent Compensation Pay is often characterized as top‑of‑market across multiple roles. The company also points to a Fair Pay Workplace certification, signaling externally reviewed pay‑equity practices.
  • Equity Value & Accessibility Equity is a meaningful part of total compensation, with new‑hire grants, refresh potential, and a discounted ESPP with a favorable lookback. Feedback suggests this ownership component materially boosts perceived total rewards.
  • Leave & Time Off Breadth Parental leave is described as up to 26 weeks paid in the U.S., paired with flexible or generous PTO and multiple leave types. Family‑building benefits and a dedicated parental‑leave hub further expand support.

Snowflake Insights

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The Company
HQ: Bozeman, MT
9,023 Employees
Year Founded: 2012

What We Do

Snowflake powers the end-to-end data lifecycle – from ingesting and processing data to analyzing and modeling it, to building and sharing data and AI applications – helping engineers, analysts, and leaders innovate faster and achieve more with their data. We're on a mission to empower every enterprise to achieve its full potential through data and AI.

Why Work With Us

Snowflake is where data does more, and so do you. More innovating, more growing, and more collaborating. Here, you’ll find the sweet spot between building big and moving fast, in technology and your career.

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