Software Engineer - GPU Kernels

Baseten

Montreal (administrative region)

On-site

CAD 254,597 - 509,194

Full time

14 days+

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Benefits offered by this job

Competitive equity
Comprehensive medical, dental, vision
Flexible PTO including Winter Break
Paid parental leave
Fertility stipend
401(k)
Exposure to ML startups

Job summary

Baseten is hiring a GPU Kernel Engineer to push the performance of state-of-the-art AI workloads. You will craft low-level kernels, optimize CUDA code and leverage tensor cores to accelerate production ML systems used by millions.

You will work on embedding and inference stacks, collaborate with researchers, and present findings to shape Baseten's acceleration platform and open-source GPU libraries.

Qualifications

  • Proficiency in GPU architecture, CUDA C++ APIs and memory optimization strategies.
  • Hands-on experience with high-performance kernels and ML workloads.
  • Strong debugging, profiling and performance tuning skills.

Responsibilities

  • Design and implement high-performance GPU kernels for ML ops (MATMUL, attention, MoE).
  • Write and optimize CUDA/assembly code with architecture-specific techniques.
  • Apply memory coalescing, warp-level programming and tensor-core acceleration.
  • Identify bottlenecks with Nsight and Torch Profiler; collaborate with research teams to productionize.

Skills

GPU programming
C++
CUDA
Performance profiling
Tensor cores
Parallel algorithms

Education

Bachelor's degree in CS/CE

Tools

Nsight Systems
Nsight Compute
Torch Profiler
Cutlass
Triton
Thrust
CUB

Job description

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.

Key Initiatives
  • Baseten Embeddings Inference: The fastest embeddings solution available
  • The Baseten Inference Stack
  • Driving model performance optimization
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 such as 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, bandwidth optimization, numerical precision and quantization strategies, and modern GPU features such as tensor cores and 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
  • 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
  • Company‑facilitated 401(k)
  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities

Compensation Range: $180K - $360K

Apply 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).

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