Machine Learning Research Engineer - Applied Research

About WindBorne Systems

WindBorne Systems enhances weather forecasting by utilizing an exclusive and advanced data source: a worldwide network of innovative smart weather balloons that capture critical atmospheric information. The company handles the design, manufacturing, and operation of its proprietary balloons and leverages the gathered data to create weather intelligence previously unattainable.

The mission is to eliminate uncertainties in weather prediction to aid humanity in adapting to climate change—whether forecasting hurricanes or accelerating renewable energy adoption. The vision includes a future where thousands of these microballoons densely monitor the planet, closing data gaps and providing crucial insights for individuals and enterprises to make informed decisions.

Founded by Stanford engineers recognized among Forbes 2019 30 under 30, WindBorne is supported by premier investors such as Khosla Ventures and Footwork VC.

WindBorne develops AI-driven weather models that operate continuously, delivering global forecasts every 20 minutes. The environment involves tackling complex research challenges that arise from diverse customer needs and novel datasets that may enhance performance in unexplored domains.

Key Responsibilities

• Address applied research problems that are not fully specified by converting real-world needs from clients, government collaborations, and internal teams into manageable machine learning tasks, experiments, and deliverables.
• Quickly prototype solutions, adjust models, process unfamiliar datasets, and experiment with new ideas. Some projects will evolve into product features, while others will guide future research direction.
• Take full ownership of projects from scoping and risk assessment to setting milestones, executing research, and communicating progress to stakeholders.
• Customize WeatherMesh models for specific regions, forecasting goals, data sources, or operational limits as needed.
• Collaborate technical aspects with external customers and research partners, ensuring clear communication and building trust through reliability and precise explanations.
• Effectively present findings via demos, reports, and technical presentations, clarifying successes and ongoing challenges.

Required Qualifications

• Proficiency in Python and PyTorch with demonstrated capability to independently adapt research code and develop functional prototypes.
• Proven experience converting loosely defined technical concepts into validated outcomes.
• Keen experimental insight and adaptability when handling imperfect datasets, vague requirements, and evolving priorities.
• Strong communication skills, enabling direct interaction with external partners without exaggeration or excessive detail.
• Flexibility to operate across research, engineering, data analysis, and project coordination roles as necessary.
• Background in weather, climate, geospatial data, scientific machine learning, government research, or deployed engineering is advantageous but not mandatory.

Compensation and Benefits

• Competitive salary ranging between $140,000 and $240,000 annually, adjusted per experience and background.
• 401(k) retirement plan.
• Dental, health, and vision insurance coverage.
• Unlimited paid time off.
• Stock option plan opportunities.
• Complimentary office snacks and beverages.

Work Location

Position based at 1600 Bridge Parkway, Redwood City, California with hybrid or in-person attendance options.