AI System Research and Development Engineer - Optimization

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified checked Jun 7, 2026

Salary

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401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source

Seniority

Mid From the posting source

Schedule

Shift type

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Weekend work

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Company

Equity

Offered Verified - SEC 10-K source

Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

AI System Research and Development Engineer - Optimization US-CA-Menlo Park, Menlo Park, California, United States 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 looking for talented System Developers and Researchers to join the Snowflake AI Research team and contribute to LLM inference and training system development, optimizations, and agentic systems. Our mission is to build the most efficient and scalable generative AI systems. Recent releases from our team include SwiftKV , an advanced inference optimization, and Arctic LLM , one of the largest open-source MoE foundation models. This is an exciting opportunity to collaborate with a world-class team, including founding members of DeepSpeed, vLLM, and TensorFlow. Together, we will push the boundaries of deep learning systems and drive cutting-edge innovations in AI. Responsibilities: - Analyze and optimize GPU kernel performance for training and inference of LLMs. - Develop and

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