Top Tech Jobs & Startup Jobs

Leads end-to-end design of AI-first consumer product experiences, from research and problem framing through prototypes and polished interfaces. Translates complex AI insights into intuitive, trustworthy workflows; conducts user research and usability testing; and collaborates with product, engineering, and data science teams on production-ready solutions. Advocates for accessible, inclusive, ethical, and transparent AI design while using Figma and AI-enabled tools throughout the design process.

Partner with product and cross-functional teams to define KPIs, build measurement frameworks, analyze experiments and launches, and deliver insights that shape product strategy and roadmap decisions. Build self-serve reporting tools, translate complex data into actionable recommendations, and develop deep product-domain expertise across AI, algorithms, hardware, and healthcare.

Design, build, and productionize scalable machine learning systems for personalized health and fitness metrics using physiological and behavioral data. Responsibilities include improving ML pipelines, translating research prototypes into reliable production services, developing operational infrastructure, implementing observability and incident response, and mentoring engineers and applied scientists.

Owns NPI quality for accessory products from concept through launch. Responsibilities include risk assessments, DFMEA, validation planning, launch readiness, quality control plans, root cause analysis, corrective actions, supplier and manufacturing collaboration, dashboards, and continuous improvement. The role partners with engineering, supply chain, deployment, support, and quality teams to ensure regulatory compliance and product quality.

Owns complex operational workstreams from planning through execution, managing project plans, risks, reporting, and stakeholder coordination. Partners across supply chain, manufacturing, hardware, quality, membership services, and business systems to improve operational performance. Analyzes data, identifies process improvements, drives issues to resolution, and delivers measurable business impact in a fast-paced environment.

Design, build, and operate WHOOP’s data platform infrastructure, including lakehouse, warehouse, and streaming systems. Improve performance, reliability, cost efficiency, observability, and developer experience across AWS-based data systems. Develop internal tools, APIs, automation, CI/CD, and infrastructure-as-code practices. Partner with data, ML, analytics, and software engineering teams to support scalable workflows, governance, and production excellence while using AI-assisted development tools effectively.

Design, build, and deliver scalable backend services powering WHOOP’s member-facing fitness, sleep, recovery, and integration experiences. Collaborate with engineering, product, design, data science, and performance science teams; translate requirements into technical plans; improve reliability, performance, testing, monitoring, and observability; and contribute through code reviews, documentation, knowledge sharing, and mentoring.

Design, develop, and maintain scalable backend services, APIs, integrations, data pipelines, automation, and workflows for internal business systems. Partner with cross-functional stakeholders to translate business needs into technical solutions. Ensure system reliability, performance, security, and scalability while contributing to technical strategy, code reviews, engineering best practices, mentorship, and process improvement.

Lead and scale design research across WHOOP Labs, shaping early-stage insights for hardware and product innovation. Manage and develop senior researchers, guide mixed-methods research prioritization, partner with cross-functional teams, oversee external vendors, and contribute hands-on to complex physical-product research. Communicate credible insights to leadership and influence product decisions across the hardware development lifecycle.

Lead operational analytics for WHOOP’s global operations, identifying inefficiencies across shipping, fulfillment, inventory, costs, and service levels. Own metrics, forecasting, spend tracking, variance analysis, and cost-reduction initiatives while partnering with Operations, Finance, Membership Services, vendors, and Data Engineering. Build trusted data assets, pipelines, semantic-layer definitions, dashboards, and performance reviews. Manage and mentor analysts while influencing strategic prioritization and resource allocation through data-driven insights.