Hardware Enablement Engineer (AI Infrastructure)

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This Jobot Job is hosted by: Grant Greenhalgh
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Salary: $180,000 - $250,000 per year

A bit about us:

We're a well-funded AI infrastructure startup developing modern software at the intersection of artificial intelligence, high-performance computing, and specialized hardware. The team is tackling complex performance challenges associated with running modern AI workloads across emerging compute architectures.

Why join us?

• Well-funded by leading tech investors
• Cutting edge technical problems with complex solutions
• Lucrative Equity in a seed stage startup
• Competitive compensation
• Excellent benefits (healthcare, vision, dental)

Job Details

We’re looking for a deeply technical systems engineer to help bring emerging AI compute platforms from early-stage hardware into production environments. This role sits directly at the intersection of hardware and software, working across multiple layers of the systems stack to enable modern AI workloads on specialized compute architectures and inference infrastructure.

What We're Looking For

• Strong systems programming experience in C, C++, Rust, or similar low-level languages
• Experience working with GPUs, AI accelerators, custom silicon, or other specialized compute hardware
• Strong understanding of hardware/software interfaces
• Experience across one or more areas including firmware, device drivers, compilers, runtimes, kernels, or low-level libraries
• Familiarity with accelerator toolchains and software enablement
• Understanding of computer architecture, memory systems, parallel computing, and hardware performance
• Experience bringing new hardware platforms or architectures into usable software environments
• Exposure to AI/ML workloads, inference systems, or high-performance computing
• Ability to debug complex problems spanning multiple layers of the hardware/software stack
• Experience with CUDA, ROCm, LLVM, MLIR, Triton, or related technologies is highly valuable

Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button.

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