Currently tracking 14 active AI roles, up 38% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $125k–$300k (avg $197k).
Whoop is actively hiring for 18 roles related to artificial intelligence. The majority of these positions are focused on application development, accounting for 33% of the listings, followed by serving infrastructure at 22% and agents at 17%. Engineering is the most frequent function for these hires. Recent activity shows a 33% increase in new AI roles over the last 30 days, with 4 new positions posted compared to the previous 30-day period.
Whoop currently has 20 active AI-related roles in our index. The most common open titles are: Associate Director, Core Algorithms (Sensor Intelligence Group), Associate Director, Machine Learning (Core Algorithms), Principal AI/ML Researcher, Senior AI Researcher (Foundation AI), Senior AI/ML Engineer (AI Platform). Most positions are in Engineering and Research.
Whoop's active AI hiring is concentrated in: application (30%), serving infrastructure (25%), agents (15%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Whoop is hiring AI talent in: United States (20 roles).
Job postings at Whoop most frequently mention: Machine Learning, Cloud Infrastructure, Software Engineering, System Design, Python.
In the past 30 days, Whoop has posted 6 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Software Engineer II, ML Ops Software Engineer II, ML Ops role at WHOOP focused on building and optimizing ML cloud infrastructure to support Data Science and AI teams in productionalizing machine learning models. Responsibilities include designing and maintaining cloud infrastructure, implementing CI/CD pipelines for ML models, developing integration components, and leveraging AWS services for scalable and cost-effective ML/AI workloads. | Serve | 7 |
| Staff Software Engineer, Machine Learning (Health) Staff Software Engineer on the Clinical Health team responsible for designing, building, and operating production systems that deliver personalized health insights using machine learning. The role involves working at the intersection of ML, backend engineering, cloud infrastructure, and SaMD, translating algorithms into production-grade systems and providing technical leadership for ML infrastructure, inference services, data pipelines, and platform architecture within a quality-managed environment. | ServePost-train | 7 |
| Technical Lead, ML Operations WHOOP is seeking a senior engineer to lead the MLOps team, owning the strategy, roadmap, and execution for a critical component of their ML platform. This hybrid role involves setting technical direction, leading a small team, driving architectural decisions, and partnering with Data Science, AI, and Engineering teams to scale ML capabilities and optimize ML infrastructure. | Serve | 7 |
| Associate Director, Core Algorithms (Sensor Intelligence Group) Associate Director of Engineering, Core Algorithms to define and lead WHOOP’s strategy for transforming physiological sensor data into real-time, production-grade intelligence. This role owns the technical vision and execution for core algorithm systems that power member-facing experiences across generations of WHOOP devices. Operates at the intersection of machine learning, signal processing, and embedded systems, defining multi-year technical direction, scaling high-performing teams, and shaping how WHOOP delivers differentiated edge intelligence at scale. Leads teams driving innovation in on-device intelligence, translating complex physiological data into scalable, high-quality insights while navigating tradeoffs across accuracy, latency, and efficiency. | ServeData | 7 |
| Senior Machine Learning Engineer (Data Science Algorithms) Senior Machine Learning Engineer at WHOOP, a health and fitness wearable company. The role focuses on designing, building, and productionizing ML systems for health and performance insights, working with physiological and behavioral data. Emphasizes strong coding, system design, and delivering production-ready ML solutions on cloud platforms. | Serve | 7 |