Senior Machine Learning Engineer, AI Platform
Whoop
San Francisco, CAOn-siteFull-time
About this role
Senior Machine Learning Engineer, AI Platform @ Whoop
Senior Machine Learning Engineer, AI Platform
Location
Boston, MA
Employment Type
Full time
Location Type
On-site
Department
Software
At WHOOP, we’re on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level and live longer by using AI to transform continuous physiological data into clear insights and actionable recommendations. Our AI platform is central to this mission, turning raw physiological signals into trusted, personalized guidance that members can act on every day.
WHOOP is hiring a Senior AI/ML Engineer to help scale the intelligence layer behind WHOOP’s AI-powered experiences, including WHOOP Coach, AI-powered Support, and new intelligent features across the product. In this role, you will own core components of the AI Platform that power our internal AI Studio: evaluation pipelines, fine-tuning workflows, LLM observability, and experimentation tooling. You will partner closely with product and data science to translate real member needs into reliable, impactful AI systems that improve continuously based on real-world usage.
RESPONSIBILITIES:
- Design, build, and operate production AI systems and scaffolding around language models that power conversational, predictive, and generative capabilities across WHOOP products.
- Lead end-to-end AI system initiatives spanning problem definition, data flows, dataset design, evaluation harnesses, deployment, and iteration in close partnership with data science and product.
- Build and maintain pipelines for collecting, curating, and reshaping messy, multi-source data into high-quality, well-structured training and evaluation datasets for language model–based systems.
- Operationalize fine-tuning and evaluation workflows for large language models behind member-facing features such as WHOOP Coach and AI Support, including defining datasets, labels, and taxonomies that reflect real member