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Develop sensor intelligence for physiological insights by owning sensor modality requirements, processing raw data, implementing signal-processing and machine-learning algorithms, designing hardware and human studies, and collaborating with hardware and firmware teams. The role requires communicating technical findings across functions while advancing sensor and product features from early concept through development.

Provides commercial legal guidance across global business operations by drafting and negotiating vendor, SaaS, technology, marketing, partnership, procurement, and services agreements. Advises stakeholders on contract, intellectual property, privacy, and compliance matters; builds scalable templates, playbooks, workflows, training, and self-service resources; and improves legal processes through automation and AI-enabled tools.

Manage WHOOP’s Mac and Windows endpoint fleets throughout the device lifecycle, from deployment through disposition. Engineer MDM, vulnerability patching, security policies, monitoring, observability, reporting, and automation aligned with HIPAA standards and SLA commitments. Reduce support tickets and manual toil, contribute to AI-first IT operations, support large-scale IT implementations, mentor colleagues, and communicate endpoint strategy clearly across technical and business teams.

Lead the technical direction and execution of WHOOP’s foundation AI modeling efforts across wearable sensor data, language, biomarkers, and behavioral signals. Drive high-risk research from hypothesis to production, shape AI strategy and infrastructure decisions, collaborate across research, product, and engineering, mentor senior technical talent, establish evaluation standards, and represent WHOOP externally through recruiting, partnerships, and the machine learning research community.

Leads WHOOP’s technical recruiting strategy and organization across engineering, product, data science, AI/ML, hardware, and other technical functions. Responsibilities include managing and developing recruiters, workforce planning, executive partnership, recruiting metrics, scalable interview processes, employer branding, talent pipelines, stakeholder advising, and implementing recruiting technologies and AI-enabled workflows. The role requires hands-on execution, strategic leadership, and relocation to the Boston office.

Lead system architecture and technical strategy for WHOOP wearable hardware platforms. Define requirements, interfaces, architecture documentation, and verification and validation strategies across electrical, mechanical, firmware, sensing, and algorithm teams. Drive technical decisions, design reviews, risk mitigation, supplier and manufacturing collaboration, and product roadmap recommendations. Mentor engineers and establish systems engineering best practices. The role requires up to 15% domestic and international travel and is based in Boston, Massachusetts.

Provide overnight support to WHOOP members through phone, email, and chat. Troubleshoot hardware, mobile app, and data-related issues; resolve or escalate concerns; document interactions; identify recurring problems; and share member feedback. The role emphasizes empathetic, personalized service, strong communication, quality and satisfaction metrics, adaptability, and continuous learning. Employees must work onsite in Limerick for 75% of the week and maintain flexible Monday-Sunday overnight shifts.

Build scalable backend services supporting growth experiments, e-commerce, and member engagement. Design and optimize APIs and infrastructure using Java, Kafka, Postgres, and AWS. Own development from requirements through deployment and monitoring, collaborate with Product, Design, Data, and Engineering teams, contribute to architecture decisions, and mentor junior engineers.

Own the AI product platform, including evaluation methodology, model and provider selection, internal tooling, adoption, and AI unit economics. Partner with engineers, researchers, and data scientists to improve quality, latency, and cost. Drive cross-functional programs, assess emerging ML techniques, and turn ambiguous opportunities into focused bets for internal productivity and member experiences.

Analyze brand marketing performance across channels, audiences, creative, and markets. Design and evaluate incrementality tests, brand lift studies, geo-lift experiments, and marketing mix models. Build dashboards and reporting frameworks, synthesize survey, media, web, and brand health data, and provide recommendations that guide creative strategy, media planning, and investment decisions. Partner with Brand Marketing, Media, Data Science, and external measurement teams.