Applied ML Engineer – Sensing & Human Motion

Verve • Cambridge, MA

3d • Hybrid

About The Position

Verve is building a world-class team to commercialize wearable solutions that empower the way people move in the world. Our first product is a lightweight, connected wearable system that can be worn all day, every day by industry associates to improve worker safety, and experience. Verve is growing and launching partnerships with some of the leading companies in the world to augment and protect their workforce and we have the unique potential to change the lives of millions of workers. Verve is dedicated to building a diverse team of individuals who are committed to contributing to an inclusive environment and value respect for all, serving the greater good, and welcoming individuals from a wide range of backgrounds, experiences, and perspectives.

Requirements

• BSc in Computer Science, Electrical Engineering, Biomedical Engineering, Robotics, or equivalent
• Understanding of signal processing, time-series analysis, and supervised classification techniques
• Experience with Python data/ML stack: scikit-learn or similar, pandas, NumPy, and at least one framework such as PyTorch, LightGBM, or XGBoost
• 5+ years of experience in applied machine learning, sensor data analysis, or quantitative engineering
• Ability to communicate and analyze test results to a broader team
• Experience in the use of analysis/measurement tools such as statistical hypothesis testing, cross-validation frameworks, and experiment tracking

Nice To Haves

• Experience designing data collection protocols and managing real-world labeled datasets is a plus
• Experience with wearable sensors, IMU data, or human activity recognition is a plus
• Experience in embedded systems / robotics / sensing / IOT is a plus
• Experience working in start-up environments building and scaling products and services is a plus

Responsibilities

• Design and execute field data collection campaigns — define sensor configurations, sampling protocols, and labeling procedures to build high-quality training datasets from real warehouse environments
• Design experiments to evaluate model performance, isolate variables, and validate hypotheses across diverse worker populations and facility layouts
• Build and maintain ML pipelines that process multi-modal sensor data (IMU, accelerometer, load cell, video) into actionable classifications and metrics
• Engineer discriminative features from time-series sensor signals and evaluate models using rigorous holdout protocols (e.g., leave-one-subject-out cross-validation)
• Develop calibration and normalization strategies that generalize across workers, devices, and deployment conditions without per-user tuning
• Translate raw sensor streams into worker safety and productivity metrics, delivered through reports and dashboards for facility operators
• Work closely with hardware and product teams to understand sensor capabilities and constraints, and feed findings back into product requirements
• Document experiments, results, and design decisions to build institutional knowledge as the team scales

Benefits

• Competitive salary and stock options.
• Generous premium coverage for medical and dental insurance.
• Unlimited PTO
• The opportunity to make an immediate impact in a fast-growing start-up and industry.
• Wear robots at work!

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 11-50 employees