Software Engineer, ML Infrastructure at WindBorne Systems

WindBorne Systems is supercharging weather models with a unique proprietary data source: constellations of next-generation smart weather balloons targeting the most critical atmospheric data. We then combine that unique data source with the world’s most accurate AI weather models. Our long-term vision 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. The founding team of Stanford engineers was named Forbes 2019 30 under 30 and is backed by top investors including Khosla Ventures.


WindBorne is looking for a Software Engineer to work on our AI-based weather forecasting infrastructure. We’re looking for generalists who love getting in the weeds, and will be hiring multiple people over the course of the next year to work on this team. You will play a pivotal role in scaling up the world’s most accurate medium range weather models.


We currently manage hundreds of terabytes of weather data, and we run compute both on-prem and in the cloud. When we started our AI based weather forecasting project about 8 moths ago, we weren’t sure it would go anywhere, and so we built a cluster of 33 4090’s to save money. Results far exceeded expectations, and we now have money to spend in the cloud, but our team is still hard-wired to operate close to the metal where possible. We are looking for people who get excited by that kind of stuff. A cornerstone of this role will be managing and being aligned with the rest of the team in balancing the following tradeoffs: (1) Being scrappy as hell vs leveraging capital to move fast and (2) Building scalable, well built infrastructure vs the absolute chaos of fast paced R&D.

You will report directly to the CEO, John Dean, as he currently is running the AI team. 


Responsibilities:
Keep the spice flowing


Skills and Qualifications:
You must be fluent in python and at least one other compiled programming language. You must have a deep systems-level understanding of linux environments. You must also be willing to learn new parts of the system that you may not have touched before in order to solve problems while pushing limits. As an example, we’ve legitimately hit RAM fragmentation problems, something the linux kernel is quite good at avoiding normally, while handling hundreds of GB of weather data in ram. You should have a good understanding of many common high performance tools in unix environments, tools such as mmap, NFS, ZFS. If you have the right experience for this job, you likely have fun war stories about weird issues that you’ve run into pushing the limits of a computational system. You don’t need to come in with 100% familiarity with the kinds of things we are doing, but you should have experience with some of it and a desire to learn a lot more.

Benefits:

• 401(k)

• Dental insurance

• Health insurance

• Vision insurance

• Unlimited PTO

• Stock Option Plan

• Office food and beverages

Location:

Address: 858 San Antonio Rd, Palo Alto, CA.

In person strongly preferred.