Software Engineer - Kernels

GW261
  • $200,000-$300,000
  • Mountain View, CA
  • Permanent

About the job


Software Engineer - Kernel Developer


Mountain View, CA


Acceler8 Talent is seeking an experienced Software Engineer with deep kernel development experience to join a well funded startup whose hardware promises to drastically change the economics of compute for the worlds' largest models.


With >$100m series A in the bank, and a genuinely world-class team with a track record of shipping highly successful products, this company abandons legacy chip design assumptions and strives for the best possible solution for every aspect of their chip - there is no such thing as "good enough".


As a Kernel Engineer, you will be responsible for designing and optimizing performance-critical kernels that interface directly with custom AI hardware. You will work closely with ML Research and Hardware Engineering teams, providing a programmer’s perspective on hardware architecture and ensuring tight integration across the software stack.


Responsibilities:

  • Design, implement, and optimize high-performance kernels that interface directly with custom AI hardware
  • Partner closely with ML Research and Hardware Engineering teams to translate algorithmic intent into efficient kernel implementations
  • Provide architectural feedback and guidance from a programmer’s perspective to influence hardware and system design decisions
  • Optimize kernels using techniques such as parallelism, SIMD/vectorization, low-level memory optimization, and instruction-level tuning
  • Support performance analysis, profiling, and debugging across kernels, runtime, and hardware


Requirements:

  • Bachelor’s degree in Computer Science or equivalent practical experience
  • Experience optimizing software for specialized or accelerator hardware, including techniques such as parallel programming, SIMD, low-level C/C++, assembly-level optimization, or GPU/CUDA programming
  • Proficiency in at least one of: Assembly, C, C++, Zig, or Rust
  • Strong understanding of performance bottlenecks across compute, memory, and data movement


Preferences:

  • Experience implementing kernels for ML workloads, including models such as Transformers
  • Familiarity with distributed and parallel execution models, including AllReduce, AllToAll, data parallelism, and tensor parallelism
  • Working knowledge of compiler fundamentals and how code is lowered, optimized, and executed on modern hardware


If you're interested in building the future of AI compute, apply here or reach out to me at ltomaszko@acceler8talent.com to discuss further.


Luke Tomaszko Senior Semiconductor & Chip Design Recruiter

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