Lead AI Infrastructure Engineer at Avride
Austin, TX
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Jul 29, 2026
Austin, TX
Sep 24, 2026
What this job asks for AI summary
This role sits within the core infrastructure team of a self-driving vehicle company, focused primarily on GPU inference performance for both onboard (near-real-time) and offboard (high-throughput) autonomous driving workloads. The engineer will own and evolve the ML infrastructure layer — starting with the GPU inference framework and expanding to broader ML pipelines — working closely with applied ML teams on neural network architecture integration.
Senior level · 5+ years · Full-time
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Rare in this occupation — lead with these, and say what you built with them.
What the occupation pays Median $138,970 (middle half $107,524–$175,762).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Aug 1, 2026. It is a model, not a headcount.
Why we read it this way (4)
Location is not explicitly stated in the posting beyond US work authorization being required and no relocation or remote being offered — the CBSA could not be determined from the text alone.
The role title is simply 'software engineer' with no seniority modifier, but the scope (owning ML infrastructure across the company, 5+ years of C++) supports a Senior classification.
'GPU programming' is derived from the hard requirements around GPU inference performance and understanding how GPUs work — the posting does not name a specific GPU framework (e.g. CUDA, TensorRT) explicitly in the requirements section.
The posting mentions C++ framework, execution graph systems, and ML pipelines as context for the team's stack but does not gate candidates on those specific sub-technologies beyond C++ and PyTorch.
Read the full posting
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