Machine Learning Research Engineer, Applied Research

WindBorne Systems is supercharging weather forecasts with a unique proprietary data source: a global constellation of next-generation smart weather balloons targeting the most critical atmospheric data. We design, manufacture, and operate our own balloons, using the data they collect to generate otherwise unattainable weather intelligence. Our mission is to eliminate weather uncertainty, and in the process help humanity adapt to climate change, be that predicting hurricanes or speeding the adoption of renewables. We are building a future in which the planet is instrumented by thousands of our microballoons, eliminating gaps in our understanding of the planet and giving people and businesses the information they need to make critical decisions. 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. Our technology creates research opportunities that do not arrive as clean benchmark problems: a customer needs a forecast tailored to a new decision, a government partner poses a difficult technical question, or a new dataset might improve performance in a domain we have never tested. We need someone who can take an underspecified, high-value problem and drive it from first conversation through research prototype and convincing result. Responsibilities What you’d own: Ambiguous applied research problems - Translate real-world needs from customers, government programs, and internal teams into tractable machine learning questions, experiments, and deliverables. Rapid technical development - Build prototypes, adapt models, analyze unfamiliar datasets, and test ideas quickly. Some projects will become product capabilities; others will answer an important question and point us toward the next one. End-to-end project ownership - Scope work, identify technical risks, set milestones, execute the research, and communicate progress. You will often be the person making sure an open-ended project reaches a useful conclusion. Model and data adaptation - Explore ways to customize WeatherMesh for particular regions, forecast targets, observation sources, or operational constraints. External technical partnership - Serve as a technical counterpart to sophisticated customers and research partners. Understand what they actually need, explain our models accurately, and build trust through clear reasoning and reliable execution. Research communication - Present results through demonstrations, reports, and technical briefings. Explain both what worked and the limitations that remain. Skills and Qualifications Requirements Strong Python and PyTorch skills, including the ability to modify research code and build working prototypes independently. A track record of taking loosely specified technical problems from idea to validated result. Strong experimental instincts and comfort working with imperfect data, incomplete requirements, and changing priorities. Excellent written and verbal communication. You can work directly with external partners without overstating results or losing them in unnecessary detail. Comfortable moving between research, engineering, analysis, and project coordination as the problem requires. Experience with weather, climate, geospatial data, scientific machine learning, government research programs, or forward-deployed engineering is helpful, but not required. Benefits 401(k) Dental insurance Health insurance Vision insurance Unlimited PTO Stock Option Plan Office food and beverages Salary $140k-$240k. We are considering a range of backgrounds and experience levels for this position and adjust our offers accordingly to be competitive with market rates. Location 1600 Bridge Pkwy, Redwood City, CA. Hybrid or in-person #J-18808-Ljbffr WindBorne Systems