About the Role
Join an early-stage agricultural technology team building an intelligence platform to help make sense of crop, soil, weather, and farm operations data. As one of the first engineers, you will take on end-to-end technical challenges and help shape the product and engineering culture.
What You'll Do
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Build data pipelines that bring together farm data from sensors, satellite and drone imagery, weather sources, and agronomic records.
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Train, evaluate, and deploy machine learning models, along with the infrastructure that supports them.
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Put product features in front of growers, observe how they work in practice, and iterate based on what you learn.
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Help choose the technology stack, establish engineering practices, and contribute to future hiring.
What We're Looking For
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Roughly 0 to 4 years of professional experience, or an equivalent record of building and shipping work.
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Strong coding ability in Python and/or TypeScript, with comfort working across the stack.
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Experience specializing in data engineering, machine learning, or AI agent development, and a record of shipping code into production for users.
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Evidence of completing substantial projects, such as research, open source, startup work, or independently built products.
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Persistence through challenging technical or personal projects, and curiosity about AI and real-world industries.
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Experience with PyTorch, computer vision, time-series, or geospatial data is a plus.
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Interest or experience in agriculture, climate, food, hard tech, or early-stage startups is welcome. Agriculture experience is not required.
Compensation & Benefits
Base salary up to $250,000 annually, plus meaningful equity. Visa sponsorship policy was not provided.
Location
On-site, five days per week in San Francisco, California, United States.
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