---
title: 'Software Engineer, Machine Learning Systems at WindBorne Systems'
canonical: 'https://feeny.ai/job/software-engineer-machine-learning-systems-windborne-systems-redwood-city-tra8tqyss8x1'
type: 'job'
last_seen: '2026-10-12'
---

# Software Engineer, Machine Learning Systems at WindBorne Systems

- **Company:** WindBorne Systems
- **Location:** Redwood City, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-09-30
- **Last confirmed live:** 2026-10-12
- **Apply:** https://jobs.ashbyhq.com/windborne-systems/50ac770b-9733-4bf6-844d-ee40f39525c5

## Job description

WindBorne Systems designs, manufactures, and operates Atlas, a global constellation of smart weather balloons. The atmospheric observations they collect help drive [WeatherMesh, our AI weather model](https://windbornesystems.com/blog/introducing-wm-6). Our model, WeatherMesh, runs 24/7, producing global forecasts every hour. Our deep learning research team is small and iterates quickly, but sometimes R&D gets ahead of the internal tools that support it. We’re looking for a talented and curious software engineer to keep model inference running reliably, process atmospheric data as it arrives, and build tools that show us what’s happening in both. In this role, you’ll work with our deep learning team and backend and frontend engineers. We have problems for you to tackle right away, and we also want someone with ideas about what to build next. You’ll help figure out what’s needed, build it, and be responsible for how it works once it’s running. Prior machine learning experience is not required! You can come in with no ML background at all and be successful. Where you lack understanding, you’ll dig into model code, ask researchers questions, and use AI tools to get up to speed. Essentially, learn what you need to build and go build it. We care much more about how well you learn and your approach to problem solving than whether you have RAG or LLM fine-tuning on your resume. [Note: We’re not trying to shade ML engineers - we have many great ones on our team. Yes, those skills can be useful in other domains, but they’re not prerequisites for this role. We’re bringing them up to emphasize that, without good software taste and a knack for learning, ML skills alone are not what we're looking for.]

## What you’ll own

- Keep forecasts running. Build the tooling that runs our weather models and detects failures. If a cloud node goes down, our systems need to recover and keep producing forecasts.
- Process atmospheric data in real time. Build pipelines for incoming observations, account for late or missing data, and make it clear when something needs attention.
- Show us what’s happening. Build tools to visualize data processing and model inference as they run. The team should be able to see how a run is progressing, where it’s slowing down, and what went wrong if it fails.

You’d be a good fit if:

- You’ve owned software in production. You’ve been responsible for a system after launch: how it performs, how it fails, and how it recovers. That experience has given you a feel for the monitoring, reliability, and operational discipline a critical system needs.
- You’ve built substantial software. You can walk us through a hard technical problem you solved, why you chose your approach, and what you learned. You’re comfortable reading unfamiliar code and tracking down bugs that involve more than one part of a system. Bonus points for good UI design and a portfolio we can see.
- You think beyond the immediate fix. You can solve today’s problem while recognizing what should become reusable infrastructure for future work. You have ideas about how to improve the systems you own and want to help decide where we go next.
- You’re curious and motivated to build. You ask questions, investigate how things work, and turn what you learn into something useful. You don’t sit idly while waiting for guidance; you can’t help but poke around.
- You use AI and agentic tools like a bandit. You use them everywhere you can: to explore code, learn about unfamiliar systems, test ideas, and build quickly. You understand the code you ship and can debug it when it doesn’t work. Most importantly, you know these tools are powerful, but you can’t outsource thinking to them entirely. After all, you’re still on the hook for what gets built.
- You want to work on a dynamic team and see your work put to use quickly.

We’re flexible on programming languages, frameworks, and years of experience. Show us what you’ve built and how you think through problems. You can learn the stack here, and honestly, things change quickly.

## Nice to have

- Experience with data pipelines, distributed systems, or infrastructure.
- Experience with scientific computing, weather data, or geospatial systems.
- Familiarity with ML inference, GPU computing, or PyTorch (again, not required).

## Compensation and location

- Base salary: $120,000–$200,000, depending on experience and scope.
- Location: In person at 1600 Bridge Parkway, Redwood Shores, CA.
- Benefits: 401(k), health, dental and vision insurance, unlimited PTO, stock options, and office food and beverages.

## About WindBorne Systems

## Company Overview
- **One-liner**: WindBorne Systems designs, builds, and operates the world’s largest constellation of autonomous, long‑duration weather balloons to capture unique in‑situ atmospheric data and deliver AI‑powered weather forecasts.
- **Entity Type**: Private (Series A – total funding $26M)
- **Headquarters**: Redwood City (Redwood Shores), California, United States
- **Founded**: 2019
- **Founders**: John Dean (CEO), Andrey Sushko (CPO), Kai Marshland (CTO)

## Core Business
- **Primary industry**: Aviation & Aerospace / Weather Intelligence
- **Target customers**: B2B, B2G – governments, utilities, airlines, renewable energy operators, and commercial enterprises with weather‑sensitive operations
- **Mission**: Build a planetary nervous system that covers 100% of the Earth, providing humanity with unprecedented environmental data and predictions to mitigate the impacts of weather uncertainty and climate change [windbornesystems.com/mission](https://windbornesystems.com/mission)

## Products & Services
- **Atlas Balloon Constellation**: A global fleet of long‑duration smart weather balloons that autonomously control altitude and provide ~50 vertical profiles per balloon, reaching remote oceans and polar regions [windbornesystems.com](https://www.windbornesystems.com/)
- **WeatherMesh**: A proprietary deep‑learning forecast model that fuses Atlas balloon data with other sources to produce forecasts that surpass the accuracy of both physics‑based and other AI models [windbornesystems.com](https://www.windbornesystems.com/)
- **Data‑as‑a‑Service (DaaS)**: Access to real‑time and historical atmospheric profiles from the balloon constellation, sold to governments and commercial partners
- **SaaS (API)**: AI‑based weather forecasts delivered via API, enabling customers to build actionable insights and automations

## Market Standing
- **Valuation / Market Cap**: Not publicly disclosed
- **Key Metric**: Total Funding – $26M across 6 rounds (including a $15M Series A, per news reports, and a $5M venture round led by the Bill & Melinda Gates Foundation in December 2024) [linkedin.com/company/windborne](https://www.linkedin.com/company/windborne)
- **Notable Investors / Partners**: Pear VC, Khosla Ventures (seed), Bill & Melinda Gates Foundation (venture round); partnerships with U.S. and international governments, private‑sector companies, and philanthropic organizations [windbornesystems.com](https://www.windbornesystems.com/)
- **Growth Signals**: 72 employees (+75.5% YoY); 38 active job postings (+1167% YoY); operations in 8 countries (US, Canada, Poland, Singapore, South Korea, Nigeria, Sweden, Kenya); hundreds of balloons launched per month with global scaling underway [linkedin.com/company/windborne](https://www.linkedin.com/company/windborne)

## Competitive Advantages
- **Proprietary data moat**: In‑situ atmospheric data from regions (oceans, poles) where other sensors are scarce – a key input for improving forecast accuracy.
- **Vertically integrated hardware & software**: In‑house design, manufacturing, and AI model development, all based in the USA.
- **First‑mover scale**: Only company operating a long‑duration, controlled‑altitude balloon constellation at this scale (Atlas).
- **Proven model performance**: WeatherMesh consistently outperforms traditional physics‑based and other AI forecast models, validated by government and commercial partners [windbornesystems.com](https://www.windbornesystems.com/)

## Strategic Focus
- Scale the Atlas constellation to permanently close atmospheric data gaps pole‑to‑pole.
- Expand federal and commercial sales (DaaS and SaaS), especially to utilities and the U.S. government.
- Advance WeatherMesh accuracy and develop new use cases in aviation routing, renewable energy grid optimization, and disaster response [windbornesystems.com/mission](https://www.windbornesystems.com/mission)

## Why Work Here
- **Planetary impact**: Every line of code and hardware design directly improves weather prediction, saves lives, and advances climate science.
- **Engineering culture**: “The Loonie Way” – high agency, obsessive problem‑solving, building from scratch, and iterating relentlessly. The team includes alumni from Project Loon, Stanford, and top aerospace/tech companies [windbornesystems.com/careers](https://windbornesystems.com/careers).
- **Hard problems**: Autonomous systems in extreme environments, real‑time data pipelines, and cutting‑edge AI.
- **Work environment**: Based in Redwood Shores, CA; technology is invented, designed, and manufactured in the US. Roles are likely on‑site (many engineering and operations positions specify location). Offices are collaborative and mission‑focused.
- **Growth**: 38 open roles across engineering, operations, business development, and more – a fast‑scaling startup with multi‑year runway [windbornesystems.com/open-roles](https://windbornesystems.com/open-roles).

## Sources
1. [windbornesystems.com](https://www.windbornesystems.com/)
2. [windbornesystems.com/careers](https://windbornesystems.com/careers)
3. [windbornesystems.com/mission](https://windbornesystems.com/mission)
4. [linkedin.com/company/windborne](https://www.linkedin.com/company/windborne)
5. [windbornesystems.com/open-roles](https://windbornesystems.com/open-roles)

## Other roles at WindBorne Systems

- [Launch Operator - Oahu](https://feeny.ai/job/launch-operator-oahu-windborne-systems-oahu-heqd17a7n70f) — Oahu, HI
- [Launch Operator-Alabama](https://feeny.ai/job/launch-operator-alabama-windborne-systems-alabama-4gje76g48nar) — Alabama
- [Regional Field Manager (Central/South America)](https://feeny.ai/job/regional-field-manager-central-south-america-windborne-systems-central-south-hq6wwyygfhp5) — Central/south, United States
- [Flight Control Operator](https://feeny.ai/job/flight-control-operator-windborne-systems-remote-s7b04n2h1nw3)
- [Senior Manufacturing Engineer](https://feeny.ai/job/senior-manufacturing-engineer-windborne-systems-redwood-city-5397fj657a1r) — Redwood City, CA
- [Launch Contractor - Uruguay](https://feeny.ai/job/launch-contractor-uruguay-windborne-systems-artigas-ppsys5pjm21j) — Artigas, Uruguay
- [Electrical Engineer Intern](https://feeny.ai/job/electrical-engineer-intern-windborne-systems-redwood-city-yxanrb2he2m7) — Redwood City, CA
- [Lead Software Engineer - Gov Platforms](https://feeny.ai/job/lead-software-engineer-gov-platforms-windborne-systems-redwood-city-kqax9vq276dy) — Redwood City, CA
- [GTM Lead](https://feeny.ai/job/gtm-lead-windborne-systems-redwood-city-2v2gtspff59v) — Redwood City, CA
- [Chief of Staff to the CEO](https://feeny.ai/job/chief-of-staff-to-the-ceo-windborne-systems-redwood-city-r8q66bc40411) — Redwood City, CA