Responsibilities : • Write and optimize compute kernels for a custom AI accelerator -- tensor operations, data movement patterns, memory hierarchy exploitation • Develop and maintain profiling ...
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Write and optimize compute kernels for a custom AI accelerator - tensor operations, data movement patterns, memory hierarchy exploitation * Develop and maintain profiling infrastructure to measure ...
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Accelerator information
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$38K - $40.6K
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$45.7K is the 25th percentile. Wages below this are outliers.
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The median wage is $51.8K / yr.
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6% of jobs
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4% of jobs
$38K
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$66.5K
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Full-time
Re-posted 5 days ago
Job description
DensityAI is a company focused on AI technology, and they are seeking a Kernel Engineer to write and optimize compute kernels for a custom AI accelerator. The role involves collaborating with architecture and compiler teams to enhance kernel performance and contribute to the kernel programming model.
Responsibilities:
• Write and optimize compute kernels for a custom AI accelerator — tensor operations, data movement patterns, memory hierarchy exploitation
• Develop and maintain profiling infrastructure to measure kernel performance against architectural targets
• Define and document shuffle patterns for ML kernel primitives across CPU-like control, tensor cores, and CUTLASS-style operations
• Drive kernel DSL design decisions — thread spawn mechanisms, register passing conventions, and memory management strategies
• Enable end-to-end kernel execution on the architectural simulator
• Collaborate with the compiler team on the MLIR dialect — your kernels are the primary validation target
• Create onboarding documentation and kernel writing guides for the broader team
Qualifications:
Required:
• C/C++ — production-grade systems code, not scripted glue. You'll write performance-critical kernels
• CUDA or equivalent accelerator programming — deep experience writing GPU kernels, understanding warp/wavefront execution, memory coalescing, shared memory optimization. The mental model transfers directly
• Computer architecture — you need to reason about pipelines, memory hierarchies, data movement costs, and how software maps to hardware
• Performance profiling and optimization — you live in profilers. Identifying bottlenecks, measuring throughput, and iterating until kernels meet targets is the core loop
• Tensor operations — practical understanding of GEMM, convolution, attention, reduction, and scatter/gather as they map to hardware
• Python — for scripting, DSL integration, and profiling automation
Preferred:
• RISC-V, x86, or ARM64 ISA experience
• MLIR or LLVM compiler infrastructure
• HPC or scientific computing background (large-scale parallel compute intuition)
• FPGA or Verilog/SystemVerilog (ability to read RTL and reason about the hardware you're targeting)
• Familiarity with CUTLASS, Triton, or similar kernel libraries
Company:
DensityAI is an infrastructure for data centers serving automotive, robotics, and industrial applications Founded in 2025, the company is headquartered in Mountain View, USA, with a team of 11-50 employees. The company is currently Early Stage.