Staff AI/ML Researcher

Responsibilities

• Design, train, and optimize large-scale multimodal foundation models integrating wearable sensor data, text, biomarkers, and behavioral data
• Conduct applied research in self-supervised learning, representation learning, and downstream task fine-tuning
• Develop scalable, distributed training pipelines for large models on high-performance compute environments
• Collaborate with MLOps, data engineering, and software engineering teams to operationalize models for production
• Partner with product teams to translate foundation model capabilities into meaningful member features
• Serve as a technical mentor for other data scientists and contribute to the technical roadmap

Requirements

• Master's or Ph.D. in Computer Science, Machine Learning, Electrical Engineering, or a related field
• 7+ years of experience in applied ML, AI research, or large-scale modeling with a track record of delivering production systems
• Expertise in modern deep learning, including transformers and multimodal model training
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
• Experience building and scaling large datasets and training models in multi-node, multi-GPU distributed compute environments
• Knowledge of reinforcement learning for post-training foundation models (e.g., PPO, DPO, GRPO)
• Strong understanding of representation learning and self-supervised methods

About the Company

WHOOP is an advanced health and fitness wearable on a mission to unlock human performance and extend healthspan. By providing members with a deep understanding of their bodies, behaviors, and daily lives, WHOOP empowers healthier choices and peak performance.