Applied ML Engineer – Sensing & Human Motion

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.

Role

• 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

You

• 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
• 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

We offer:

• 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!

This is an in-office role though we are flexible on WFH and most people work remotely one or two days per week.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race religion color national origin gender sexual orientation age marital status veteran status or disability status.

Feeling uneasy that you havent ticked every box Thats okay weve felt that way too. Studies have shown women and minorities are less likely to apply unless they meet all qualifications. We encourage you to break the status quo and apply to roles that would make you excited to come to work every day.