Machine Learning Research Engineer, Model Evaluation at WindBorne Systems
Palo Alto, CA
$140,000–$240,000from the description
Jul 12, 2026
Palo Alto, CA
Jul 21, 2026
What this job asks for AI summary
This role centers on building and owning the evaluation framework for AI-driven global weather forecast models. Day-to-day work spans designing scientifically rigorous comparison strategies, creating fast feedback tools for researchers, developing reusable evaluation infrastructure, and communicating model performance clearly to varied audiences. It suits someone with strong ML experimentation instincts and experience working with large scientific or geospatial datasets; a background in weather or climate science is useful but not required.
Senior level · San Francisco-Oakland-Berkeley, CA · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 4 times — it's one opening, so apply once.
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 1,800 people in the San Francisco-Oakland-Berkeley, CA area plausibly meet what this posting asks for (data scientists). range 650–2,800
Applicant volume Heavy — This req sits in a large pool with little in its requirements to thin it, and auto-apply tools fire at everything in the occupation. Applying early and leading with the rare skills below is what gets read.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $173,851 (middle half $133,298–$217,653). 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 Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
The role sits at the boundary between ML research and data science: the primary day-to-day work is designing and running model evaluations, building evaluation infrastructure, and synthesizing scientific results — closer to 15-2051 (Data Scientists) than pure software development, though significant systems-building is also expected. 15-1252 is noted as a plausible alternative given the emphasis on building reusable evaluation infrastructure.
PyTorch, NumPy, pandas, and xarray are listed together as a single illustrative set ('such as … or'); PyTorch is used as the primary name with the others captured as alternatives, since the JD treats them as interchangeable examples of 'scientific and ML tools' rather than distinct hard gates.
Experience with weather, climate, forecasting, physical science, or AI-assisted research tools is explicitly called 'helpful, but not required' — treated as preferred.
The 'agentic AI-based tools' responsibility implies familiarity with LLM-based tooling; this appears only in the responsibilities narrative rather than a requirements section, so it is treated as preferred.
The posting specifies 'Hybrid or in-person' at Redwood City, CA — fully remote is not available. Redwood City falls within the San Francisco-Oakland-Berkeley, CA CBSA.
No minimum years of experience are stated at the role level; the wide $140k–$240k salary band reflects that the company considers a range of backgrounds and experience levels.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): weather/climate domain knowledge.
Read the full posting
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