Machine Learning Research Engineer, Model Evaluation

About the role

Machine Learning Research Engineer, Model Evaluation Machine Learning Research Engineer, Model Evaluation apply now WindBorne Systems is supercharging weather forecasts with a proprietary data source: a global constellation of next-generation smart weather balloons targeting critical atmospheric data. We design, manufacture, and operate our own balloons, using their observations to generate otherwise unattainable weather intelligence. Our mission is to eliminate weather uncertainty and help humanity adapt to climate change—whether by predicting hurricanes or speeding the adoption of renewables. The founding team of Stanford engineers was named Forbes 2019 30 Under 30 and is backed by top-tier investors, including Khosla Ventures and Footwork VC. WindBorne builds AI weather models that run 24/7, producing global forecasts every 20 minutes. Evaluating these models is much harder than producing a headline accuracy number: performance varies across regions, lead times, weather regimes, and customer use cases, while standard metrics often fail to capture what makes a forecast meteorologically sound or useful. We need someone with excellent scientific taste to determine where our models excel, where they fail, and which results we should trust. You will work at the intersection of machine learning and meteorology, combining fast analyses with robust systems that make future research faster and more reliable. ‍ Snapshot of the balloon constellation ON MARCH 31, 2026

Responsibilities Evaluation strategy — Work with our Meteorology team to develop a rigorous, meteorologically valid strategy for comparing WeatherMesh with leading AI and physics-based models. Choose the metrics, datasets, baselines, and case studies that provide an honest picture of forecast quality. Fast feedback and durable systems — Build quick evaluations that give researchers useful signals, then turn recurring analyses into reliable, reusable infrastructure. Think systematically about reproducibility, provenance, and how evaluation tools fit into the broader research workflow. Agentic tooling for evals — Improve our existing evaluation infrastructure, including agentic AI-based tools for investigating forecasts and synthesizing results. Technical communication — Produce clear scorecards, visualizations, and explanations for researchers, leadership, customers, and external partners. Communicate model performance precisely, including uncertainty and important caveats. ‍ Skills and

Qualifications Excellent scientific judgment and healthy skepticism. You ask whether a comparison is fair, what else could explain a result, and what evidence would change your mind. Strong experimental taste: you can identify the evaluation that answers the question that matters and distinguish robust improvement from noise. Systems thinking: you can solve today’s problem while recognizing what should become reusable infrastructure for future work. Experience evaluating ML systems using large, scientific, geospatial, multidimensional, or time-series datasets. Strong Python skills and experience with scientific and ML tools such as PyTorch, NumPy, pandas, or xarray. Able to investigate ambiguous results independently, synthesize evidence, and communicate conclusions clearly. Experience with weather, climate, forecasting, physical science, or AI-assisted research tools is helpful, but not required. ‍ ‍

Benefits 401(k) Dental, health, and vision insurance Unlimited PTO Stock Option Plan Office food and beverages ‍ Salary $140k–$240k. We consider a range of backgrounds and experience levels and adjust offers to be competitive with market rates. Location 1600 Bridge Pkwy, Redwood City, CA. Hybrid or in-person. ‍ What our hardware looks like Home Products Platform Observations Forecasts Solutions Industries Energy Trading Utilities Resources Blog FAQ Benchmarks API Docs Company Mission Careers Community Launches Contact Sign In WindBorne Systems is based in Redwood Shores, California. Our technology is invented, designed, and manufactured in the USA. © 2026 by WindBorne Systems Legal

About WindBorne Systems

WindBorne develops, manufactures, and operates a network of long-duration smart weather balloons. The company collects atmospheric data for weather forecasting, climate research, and environmental monitoring. The company uses high-altitude balloons equipped with sensors to gather data from various layers of the atmosphere. These balloons can capture precise and comprehensive atmospheric measurements. By providing high-resolution atmospheric data, WindBorne Systems contributes to more accurate weather predictions, which can help mitigate the impacts of severe weather events.

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Job details

Company

NameWindBorne Systems
IndustryAgriculture
Team Size3

Funding

Total raised

$25M

Last stage

Series A

Investors

Khosla Ventures
Footwork VC
Pear VC
CConvective Capital
Ubiquity Ventures

Founders

JD

John Dean

Co-Founder & CEO

LinkedIn
Kai Marshland

Kai Marshland

Co-Founder & CPO

LinkedIn
Andrey Sushko

Andrey Sushko

Co-Founder & CTO

LinkedIn

What happens next.

No applications, no recruiter spam. Just the intro.

01

Confirm the fit

A few questions to make sure this role is the right shape for you. Two minutes.

02

I pitch you to the company

I write the intro, send it to the founder, and handle the back-and-forth.

03

A meeting lands on your calendar

If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.