remote

Salary
$130,000–$160,000from the description
Posted
Aug 16, 2026
Location
—
Last confirmed open
Sep 25, 2026

What this job asks for AI summary

This role centers on designing and optimizing GPGPU and AI inference libraries built on Vulkan SC drivers, targeting embedded GPU platforms such as Arm Mali and Intel architectures. The engineer leads end-to-end library development — from architecture through certification — handles platform porting and release efforts, and maintains AI model testing infrastructure. The position also involves mentoring teammates and collaborating cross-functionally with product management and architecture teams.

Senior level · 5+ years · Remote · Bachelor's required · Full-time

Must have (2)
C++ or C · 5+ yrsPyTorch, ONNX or TensorFlow
Nice to have (3)
Vulkan, OpenGL, OpenCL or CUDAVxWorks or DeosDO-178 or Iso 26262

“or” means any one of them counts — you don't need all of them.

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

Roughly 6,000 people nationally plausibly meet what this posting asks for (software developers). range 3,550–12,900

Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.

What gives you an edge
PyTorch9%ONNX9%TensorFlow9%

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). This posting is about at that midpoint.

Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Aug 20, 2026. It is a model, not a headcount.

Why we read it this way (6)

The role is open to candidates in both the US and Canada. The posted USD compensation ($130K–$160K/year) applies to US-based candidates; Canadian candidates are offered $110K–$140K CAD/year. Only the USD range is captured in the compensation fields.

The ML frameworks (PyTorch, ONNX, TensorFlow) are listed together under a single required bullet ('ML frameworks such as…'). The 'such as' qualifier means any one of these satisfies the requirement, so they are captured as interchangeable alternatives rather than three independent hard gates.

The GPU programming APIs (Vulkan, OpenGL, OpenCL, CUDA) are listed under the Preferred section and are marked accordingly, despite Vulkan SC being central to the role's day-to-day work as described in the narrative.

Real-time safety-critical OS experience (Lynx, Deos, VxWorks) and safety standards (DO-178, ISO 26262) are explicitly listed as Preferred and are marked accordingly.

The alt SOC (15-2051 Data Scientists) is noted because the role has a meaningful AI/ML inference focus, but the primary work is clearly software library development in C/C++ on embedded GPU platforms, making 15-1252 the stronger fit.

Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): embedded software development.

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