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JobsBaseten

GPU Kernel Engineer

Baseten

GPU Kernel Engineer

Baseten

San Francisco

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Parental leave

Generous paid time off and holidays

401(k) matching

Professional development budget

Competitive salary and equity package

Parental Leave

Learning

Equity

Required Skills

Node.js

TypeScript

PostgreSQL

ABOUT BASETEN

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $300M Series E https://www.baseten.co/blog/announcing-baseten-s-300m-series-e/, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products.

THE ROLE:

We’re seeking a GPU Kernel Engineer to join our team at the cutting edge of AI acceleration, where your code directly impacts the performance of state-of-the-art machine learning models. As a GPU Kernel Engineer, you'll craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications.

You'll work in a fast-paced, intellectually stimulating environment where technical excellence is paramount and your contributions directly influence production systems serving millions of users across numerous products. This role offers exceptional growth potential for engineers passionate about low-level optimization and high-impact systems work.

EXAMPLE INITIATIVES

You'll get to work on these types of projects as part of our Model Performance team:

  • Baseten Embeddings Inference: The fastest embeddings solution available https://www.baseten.co/blog/introducing-baseten-embeddings-inference-bei/

  • The Baseten Inference Stack https://www.baseten.co/resources/guide/the-baseten-inference-stack/

  • Driving model performance optimization https://www.baseten.co/blog/driving-model-performance-optimization-2024-highlights/

RESPONSIBILITIES:

Core Engineering Responsibilities:

  • Design and implement high-performance GPU kernels for key ML operations, including matrix multiplications, attention mechanisms, and mixture-of-experts routing

  • Write and optimize code using CUDA, PTX assembly, and architecture-specific techniques

  • Apply advanced performance optimization methods such as memory coalescing, warp-level programming, tensor core acceleration, and compute/memory overlap

Performance & Innovation:

  • Implement cutting-edge features like quantization (FP8/FP4), sparsity, and compute/communication overlap

  • Identify and resolve performance bottlenecks using tools like Nsight Systems, Nsight Compute, and Torch Profiler

  • Collaborate with research teams to productionize theoretical advancements

Impact & Collaboration:

  • Contribute to internal and open-source GPU libraries

  • Present technical contributions at industry conferences (e.g., NVIDIA GTC, AWS re:Invent)

REQUIREMENTS:

  • 1–5 years of experience in CUDA development

  • Strong understanding of GPU architecture and programming paradigms:

  • Memory hierarchy (global, shared, registers, L1/L2 cache)

  • Thread/block/grid organization

  • Synchronization techniques and race condition mitigation

  • Proficient in C++ and GPU performance profiling tools

  • Knowledge of:

  • CUDA C++ API

  • Memory access patterns and bandwidth optimization

  • Numerical precision and quantization strategies

  • Modern GPU features (e.g., tensor cores, async operations)

NICE TO HAVE:

  • Experience with Transformer models and attention optimization (e.g., Flash Attention)

  • Familiarity with GPU kernel libraries: Cutlass, Triton, Thrust, CUB

  • Background in GEMM tuning and distributed/multi-GPU compute

  • Contributions to open-source GPU projects

  • Research publications or conference presentations on GPU performance

BENEFITS:

  • Competitive compensation, including meaningful equity.

  • 100% coverage of medical, dental, and vision insurance for employee and dependents

  • Generous PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)

  • Paid parental leave

  • Company-facilitated 401(k)

  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.

At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

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About Baseten

Baseten

Baseten

Series C

Baseten provides a platform for deploying and scaling machine learning models in production environments. The company offers infrastructure and tools for ML engineers to build, deploy, and monitor AI applications.

51-200

Employees

San Francisco

Headquarters

$1.0B

Valuation

Reviews

3.8

41 reviews

Work Life Balance

3.5

Compensation

4.0

Culture

3.9

Career

4.0

Management

3.6

73%

Recommend to a Friend

Pros

Supportive team and management

Opportunity for career growth

Good work-life balance and flexible environment

Cons

Career progression could be clearer

Internal communication could improve

Work-life balance varies by team

Salary Ranges

0 data points

Junior/L3

L2

L3

L4

L5

L6

Junior/L3 · Recruiter

0 reports

$183,600

total / year

Base

-

Stock

-

Bonus

-

$156,060

$211,140

Interview Experience

52 interviews

Difficulty

3.3

/ 5

Duration

14-28 weeks

Offer Rate

42%

Experience

Positive 66%

Neutral 21%

Negative 13%

Interview Process

1

Phone Screen

2

Technical Interview

3

Hiring Manager

4

Team Fit

Common Questions

Technical skills

Past experience

Team collaboration

Problem solving