Level

Baseten

Software Engineer - GPU Kernels

Baseten is hiring a Software Engineer - GPU Kernels for a remote role open to applicants in United States. It pays $180k-$360k a year and Level rates it ; you can apply on Baseten.

Level's read on this job

  • Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
  • The listed pay starts 7% above the typical software engineer posting on Level.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include Cursor, Clay and AI research.
  • Level lists 106 other open roles at Baseten.

AI in this role

cursorclay
ai-research

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 $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn 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:

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

  • 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

  • (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents

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

  • Paid parental leave

  • Fertility and family-building stipend through Carrot

  • (U.S. only) 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.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

How we rate this

Software Engineer - GPU Kernels at Baseten 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.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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

AI ResearchCursorClay

Also common in software engineer jobs at this level

Pay

This job starts at
$180k
Typical software engineer job
$168k

This posting starts 7% above the typical software engineer job. See software engineer jobs

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Walk me through how you've used Cursor in your day-to-day work.
  3. What are the limits of Clay that you've run into, and how did you work around them?
  4. How would you decide a model or AI system is ready to ship?
  5. 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 Research, Cursor, and Clay. 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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