Machine Learning Engineer
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Location: Burlingame, CA (Onsite)
Duration: 12+ Months
What you will do:
1. You will be responsible for building high performing health devices and systems.
2. Gather data from various sources, clean, and prepare for analysis
3. Create and redefine Client algorithms to solve problems.
4. Train Client models to use prepared data, conduct experiments, record findings, and evaluate model performance.
5. Conduct testing of Client models in various scenarios to perform in different environments.
6. Monitor the performance of deployed models, issues, and necessary adjustments to improve efficiency.
7. Work closely with XFN partners including data, software & hardware engineers, project managers and other internal and external stakeholders.
Mandatory Skills:
1. 4+ years of relevant experience.
2. Experience with end-to-end solutions, solving ambiguous problems.
3. Fluency in programming with Python; experience with PANDAS, Numpy and PyTorch.
4. Prior experience developing models for low-resource edge devices (Wearables, Mobile devices)
Highly Preferred Skills:
1. Experience with health tech, consumer products
2. Experience working with hardware acceleration (e.g., GPU, DSP, Client accelerator, CPU kernel library)
Good to have:
1. Prior experience developing models based on input data from sensors typically used on personal-compute devices (accelerometer, gyro, PPG, pressure, microphone, temperature etc).