Biosignal ML Engineer / Data Scientist
San Francisco, CAFull-time$150–225K/yrSeen todayStill listed today
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Job overview
Preload builds a data layer for physical AI, capturing human interaction through wearable multimodal sensors and turning it into datasets for robotics teams. The Biosignal ML Engineer / Data Scientist will develop features and models from raw biosignals, align and fuse multimodal streams, and help define data quality and collection priorities. The role is part of an early, in-person team in San Francisco.
Skills & qualifications
Skills
Qualifications
Full job description
About Preload Preload builds the data layer for physical AI. Robots learn mostly from video, but human interaction is much richer: touch, force, and muscle activity. We build a wearable multimodal stack (egocentric video, tactile gloves, EMG) to capture how people actually interact with the physical world, and turn it into datasets robotics teams can train on. We're a YC (F26) team of PhD founders from Johns Hopkins and Caltech with backgrounds at Neuralink, Paradromics, and other neurotech companies. The role You'll turn raw, noisy biosignals into features and models that make our data useful for physical AI. What you'll do
- Build feature extraction pipelines for EMG, tactile, and kinematic signals
- Time-align and fuse multimodal streams (video, touch, muscle activity)
- Develop models and representations of human manipulation and motor intent
- Define data quality metrics and help shape what we collect next
- Work closely with sensor and robotics teammates to close the loop from hardware to model
What we're looking for
- 2+ years working with time-series or biosignal data (EMG, EEG, IMU, neural recordings, or similar)
- Strong Python and ML fundamentals (PyTorch or similar)
- Solid signal processing skills: filtering, artifact removal, synchronization
- Experience with multimodal or self-supervised learning is a plus
- Background in neuroengineering, BME, robotics, or related fields is a plus
Why join Early, in-person team in San Francisco. You'll own core technical decisions from day one.
How this job compares
Set against the 6,070 open Machine Learning Engineer jobs on Olive Jobs, counted November 10, 2026.
- Pay
- This posting$150–225K/yr
- California median$176–261K/yr1,364 salary ranges
- US median$149–245K/yr5,010 salary ranges
This range's midpoint, $188K, is 15% below the California median midpoint ($220K) — in the lowest quarter of Machine Learning Engineer salary ranges in California.
- Openings
- Olive Jobs lists 1,783 open Machine Learning Engineer jobs in California and 6,070 across the US. 7% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 2 years of experience — less than three in four Machine Learning Engineer postings that state a minimum ask for (median 5 years, across 4,885 postings).
- Education
- 1,990 of the 6,070 open Machine Learning Engineer jobs (33%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 10, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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