ML Engineer at Open Orion, Inc.
San Francisco, CA
—
Jul 28, 2026
San Francisco, CA
Jul 29, 2026
What this job asks for AI summary
An early-stage ML engineering role at a startup building AI tools for engineering design and simulation. The work centers on designing agentic AI pipelines, generative models for structured/geometric outputs, and surrogate models that approximate expensive computational processes. Strong ML fundamentals are the core requirement; domain knowledge in geometry, physics, or CAD/CAE is a bonus.
Senior level · Remote · Full-time
“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 2,850 people nationally plausibly meet what this posting asks for (data scientists). range 1,200–4,300
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 29, 2026. It is a model, not a headcount.
Why we read it this way (8)
No location is specified anywhere in the posting; the role appears to be remote or location-flexible, but this is not explicitly stated — remote=true is inferred from the absence of any office/location requirement.
No total years of experience are stated; seniority is inferred from the scope of ownership, ambiguity tolerance, and breadth of ML fundamentals required.
The SOC code is a close call: the role is framed as 'ML engineer' with heavy software-engineering expectations (production pipelines, open-source tooling), which could support 15-1252 Software Developers. However, the primary day-to-day work — building generative models, surrogate models, agentic AI pipelines, and reasoning systems — is more squarely ML/data science (15-2051).
Salary is described only as 'competitive' with equity; no figures are provided.
PyTorch is listed as the first named ML framework alongside JAX and TensorFlow as interchangeable alternatives under a single 'at least one' requirement.
Structured prediction and 3D/scientific ML experience are listed as must-haves but name no specific tool or framework, so they are omitted per the no-generic-concepts rule; the concrete 3D techniques (point clouds, implicit representations, graph neural networks) are captured as preferred skills.
CAD/CAE workflows, simulation tools, geometry kernels, and engineering domain knowledge (aerospace, mechanical, civil) are listed under 'Strong pluses' but name no specific software product, so they are omitted as generic domain knowledge rather than named technologies.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): physics-informed neural networks.
Read the full posting
The employer publishes the full description on their own site — read it there ↗. Or sign in to read it here — it's free, and it also lets you track this application.