- Location
- San Francisco, California, US
- Workplace
- Remote
- Type
- Full-time
- Department
- Engineering
- Source
- Y Combinator
Description
About Ohm
Ohm is an enterprise AI platform that helps Fortune 100 engineering teams transform how they develop, test, and validate physical products.
Cursor and Claude Code reimagined how software products are developed. Our mission is to address the next frontier: bringing that same shift to how physical products are developed.
Every complex physical product - a battery cell, an electric vehicle, a wearable device - is developed through a process that generates enormous quantities of data, almost none of which is used to its potential. This is precisely the kind of problem modern AI is suited to solve.
We are recruiting exceptional scientists, engineers, and operators to join our mission to reimagine how products are engineered in the next decade.
Ohm is backed by Y Combinator and other world-class investors, as well as serial founders and builders.
About the role
As an Applied Machine Learning Engineer, you will take end-to-end ownership of complex machine learning and data science problems across the physical AI space. This is a high-impact role for someone with a strong technical foundation and a generalist mindset who can move from problem framing and experimentation through deployment and ongoing support.
You will work directly with the founder, the Head of Engineering, and engineering teams at Ohm's customer accounts. The role blends research depth with practical delivery, and requires someone who can align stakeholders and communicate technical decisions clearly.
What you'll do
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Own machine learning problems end to end - from problem framing and experimentation through deployment and ongoing support in live customer environments.
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Work closely with engineering, product, and client-facing teams to turn machine learning methods into production-ready solutions that can be trusted in real customer environments.
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Build and support models running in production, where their output drives real engineering decisions.
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Communicate technical decisions clearly to technical and non-technical audiences, and align stakeholders around them.
What you'll need
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Applied ML experience. 3+ years in data science, machine learning, or applied AI, with evidence of delivering high-impact production ML systems.
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STEM foundation. A background in engineering, physics, chemistry, or another STEM discipline connected to complex physical systems.
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Real-world data fluency. Experience working with sparse, noisy, time-series, or high-dimensional datasets from engineering labs or other applied environments.
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Cross-functional communication. Comfortable working with engineering, product, and customer-facing teams, and able to explain technical decisions clearly to different audiences.
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AI-native. You use AI coding tools as your primary workflow, and have thought carefully about where AI can accelerate applied ML work.
What will set you apart
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Experience building or experimenting with agents or autonomous systems.
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Domain exposure to hardware development, test and/or validation.
Wondering if you're a good fit? We believe in investing in our teammates, and value candidates who can bring their own diverse experiences to our teams, even if you aren't a 100% skill or experience match. If some of what we've outlined above describes you, we'd love to hear from you.
