Machine Learning Engineer at WindBorne Systems
Palo Alto
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 Machine Learning Engineer to work on our AI-based weather modeling. 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.
You will report directly to the CEO, John Dean, as he currently is running the AI team.
Responsibilities
You will be working on all parts of our AI models: Architecting, Implementing, Training, and Evaluation. This role is ultimately fairly open ended and responsibilities can somewhat match the specific interests of the candidate, so long as it aligns with the needs of the company and you are highly competent and willing to work hard. 95% of the machine learning stack is built by the CEO and another cofounder, and if you can do any aspect of it better than we can, you can own it. Our current high-level architecture works quite well, but it needs to be scaled up further and there is lots more fine tuning and modification to training required. In addition, there is a lot of near-term work to be done in evaluating and running case studies of existing models. We also would like to publish parts of our work and get our metrics posted to public benchmarks. We want to continue to build new architectures and models to cover other areas of the weather prediction stack.
Skills and Qualifications
You must be fluent in python and at least one other compiled programming language, and generally be a strong programmer capable of holding a pure Software Engineering job. You must have a strong background in applied math generally, and specifically in information theory, statistics, and numerical optimization. You must have experience working with deep learning models, and you should have experience training large models but this is not an absolute requirement. You do not need any background in weather, but you must be highly interested and motivated to learn about numerical weather prediction and about how weather works in general. Ideally, you are the kind of ML person who feels Fremdschämen when another ML person makes a rookie mistake while applying ML to some other field.
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture Deep Learning Engineering Machine Learning Mathematics Python Statistics
Perks/benefits: 401(k) matching Career development Equity Health care Unlimited paid time off
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