AI Applied Scientist, Snowflake

Code Intelligence

$200-287.5k

This role is eligible to participate in Snowflake’s bonus and equity plan

Python

Snowflake

PyTorch

Junior, Mid and Senior level

San Francisco Bay Area

3-5 days a week in office ( Menlo Park, CA)

AI Data Cloud for data sharing and app building

Be an early applicant

AI Data Cloud for data sharing and app building

1001+ employees

B2BArtificial IntelligenceData storageEnterpriseAnalyticsMachine LearningSaaSData AnalysisCloud ComputingData Sharing

Be an early applicant

$200-287.5k

This role is eligible to participate in Snowflake’s bonus and equity plan

Python

Snowflake

PyTorch

Junior, Mid and Senior level

San Francisco Bay Area

3-5 days a week in office ( Menlo Park, CA)

1001+ employees

B2BArtificial IntelligenceData storageEnterpriseAnalyticsMachine LearningSaaSData AnalysisCloud ComputingData Sharing

Company mission

On a mission to mobilize the world's data.

Job

Company

Role

Who you are

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
Bonus (nice to have—not all required): 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

What the job involves

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
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

Our take

Developed as a fresh alternative to the archaic systems of data governance and information silos, Snowflake is a frictionless cloud data platform that removes the barriers preventing organisations of all sizes from unleashing the true value of their data.

The company equips organizations with a single, integrated platform that offers the only data warehouse built for the cloud; instant, secure and governed access to their entire network of data; and a core architecture to enable many types of data workloads, including a single platform for developing modern data applications.

Major competitors include Azure, SQL and AWS, and Snowflake has managed to keep ahead of the competition, cementing itself as a global force. Across its 1300+ partners, the company's cloud manages over 250PB of data (with more than 515 million data workloads running every day). Its continued focus on product R&D and partnership expansion have Snowflake well-positioned to manage itself amidst the competition.

Freddie

Company Specialist at Welcome to the Jungle

Insights

Top investors

37% employee growth in 12 months

Glassdoor (3.8)

Company

Funding (last 2 of 9 rounds)

Feb 2020

$479m

LATE VC

Oct 2018

$450m

LATE VC

Total funding: $1.4bn

Company benefits

Comprehensive health insurance plans
Health savings accounts
Robust retirement plans
Life and disability insurance
Weekly online lunch and learns
Virtual workout classes
Ergonomic work-from-home equipment
On-demand mental health and wellness programs
Fertility benefits and family planning resources
Generous time-off and various leave plans
Onsite and Remote Work
Employee discounts and pre-tax selections
New hire equity + Employee Stock Purchase Plan (ESPP)
Quarterly bonus or commission program

Company HQ

Menlo Park, CA

Leadership

Benoit Dageville

(Co-Founder & President of Product)

Benoit, a leading expert in parallel execution and self-tuning databases, founded Snowflake after 10+ years at Oracle as a lead architect. He holds a PhD in Computer Science and has 270+ patents.

Thierry Cruanes

(Co-Founder)

Thierry is a leading expert in query optimization and parallel execution. He has a PhD in Computer Science with a focus in Database Systems and is a named inventor on 200+ patents.

Sridhar Ramaswamy

(Chief Executive Officer)

Sridhar joined Snowflake in 2023 via the Neeva acquisition as SVP of AI and later became CEO. He co-founded Neeva and previously led Google’s Ads business, growing it from $1.5B to $100B.

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