Senior Machine Learning Research Engineer

Responsibilities

• Design and train deep-learning and machine-learning models to extract insights from large repositories of time-series and biosensor data
• Stay up to date with the latest advancements in DL research and technologies
• Support documentation of algorithms for regulated health features
• Write clean, efficient, and maintainable code
• Monitor and ensure the proper functioning of algorithms across a diverse user population
• Conduct experiments, perform rigorous testing, and optimize models for deployment in production systems
• Collaborate with SIG, Data Science, and Firmware teams to translate research prototypes into scalable ML inference systems

Requirements

• Master's or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, Data Science, AI, Statistics, or a related field
• Published research papers in ML/DL domains, preferably involving biomedical data
• 4+ years of ML/DL research experience (or 2+ years post-PhD)
• Proficiency in Python and the scientific stack
• Strong experience with time series data and signal processing concepts
• Experience with deep learning frameworks such as PyTorch or TensorFlow
• Strong communication and collaboration skills for working across cross-functional teams

Preferred Qualifications

• Experience developing or supporting regulated or high-risk ML systems (e.g., digital health or SaMD)
• Experience in training, fine-tuning, or deploying Foundation AI models
• Experience with cloud computing platforms such as AWS or GCP

About the Company

WHOOP is on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives via wearable technology.