Machine Learning Engineer / UNICORN / Hybrid in SF

Motion Recruitment; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Medical, Dental, and Vision Insurance

Generous PTO

Equity Participation

Career Development Opportunities

Paid Holidays

Job summary

Motion Recruitment seeks a Machine Learning Engineer to join a health technology company’s R&D team. You will build advanced ML systems powering wearable health products, handling Python, TensorFlow/PyTorch, Spark, and large physiological datasets to extract meaningful consumer health insights.

This is a zero-to-one opportunity to invent new sensing capabilities, develop multimodal AI solutions, and influence future health tech roadmaps with ownership, rapid growth, and production-ready research.

Qualifications

• 3+ years of ML engineering experience.
• Strong Python development experience.
• Experience with TensorFlow and/or PyTorch.
• Background with sensor, wearable, physiological, or time-series data.
• Experience developing and deploying ML models.
• Understanding of signal processing techniques.
• Strong mathematical and statistical foundations.
• Bachelor's degree in CS/Engineering/Math/Data Science or similar.

Responsibilities

• Develop and deploy ML models for wearables and health sensors.
• Invent and prototype multimodal sensing capabilities.
• Collaborate with R&D to influence product roadmap.
• Work with large-scale physiological datasets to derive insights.

Skills

Python

TensorFlow

PyTorch

Sensor data

Time-series data

ML model deployment

Signal processing

Mathematics & stats

Education

Bachelor's degree (CS/Engineering/Math/Data Science)

Job description

A health technology company at the top of their industry is seeking a Machine Learning Engineer to join its research and development team. This full-time opportunity offers the chance to build advanced machine learning systems that power next-generation wearable and sensor-based health products. The team works heavily with Python, TensorFlow, PyTorch, Spark, signal processing, and large-scale physiological datasets to create meaningful consumer health insights.

This is a true zero-to-one engineering opportunity. Rather than maintaining existing models, this individual will help invent entirely new sensing capabilities, develop multimodal AI solutions, and influence the future roadmap of emerging health technologies. The organization values innovation, scientific rigor, and collaboration while providing significant ownership, rapid career growth, and the opportunity to see research move directly into production products used by customers worldwide.

Required Skills & Experience

• 3+ years of machine learning engineering experience
• Strong Python development experience
• Experience with TensorFlow and/or PyTorch
• Background working with sensor, wearable, physiological, or time-series data
• Experience developing and deploying machine learning models
• Understanding of signal processing techniques
• Strong mathematical and statistical foundations
• Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or similar

Desired Skills & Experience

• PhD in Machine Learning, AI, Computer Science, Statistics, Biomedical Engineering, or related field
• Publications in top-tier ML conferences or journals
• Experience with self-supervised learning
• Experience with multimodal machine learning
• Consumer wearable or medical device industry experience
• Spark or distributed computing experience
• Experience working with production-scale data pipelines

What You Will Be Doing

Tech Breakdown

• 40% Machine Learning Development
• 25% Signal Processing & Sensor Analytics
• 20% Data Engineering & Spark
• 15% Research & Experimentation

Daily Responsibilities

• 80% Hands On Engineering
• 20% Team Collaboration

The Offer

• Competitive Salary
• Equity Program

You Will Receive The Following Benefits

• Medical, Dental, and Vision Insurance
• Generous PTO
• Paid Holidays
• Equity Participation
• Career Development Opportunities

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

Posted By:

Charles Deuter