Senior Machine Learning Engineer, AI Platform

Whoop
Boston
Workplace: OnsiteFull timeUSD 150,000 - 210,000 annuallyFunction: Data Science & Machine LearningExperience: 3+ yearsSkills: ["Communication","Collaboration","Mentoring","Influencing","Problem-solving"]

Build and operate production AI systems powering WHOOP’s AI experiences, including evaluation pipelines, fine-tuning workflows, LLM observability, and experimentation tooling. Own end-to-end initiatives from problem definition and data flows to dataset design, evaluation harnesses, deployment, and continuous iteration. Create robust pipelines for multi-source data to produce high-quality training/evaluation datasets, and establish feedback loops that improve models based on real member behavior.

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FursaFursa
Whoop
Whoop
2 weeks ago

Senior Machine Learning Engineer, AI Platform

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Source: Company careers pageValidated by: Fursa AI
Last checked: 8 hours agoStatus: Live

Job Summary

Build and operate production AI systems powering WHOOP’s AI experiences, including evaluation pipelines, fine-tuning workflows, LLM observability, and experimentation tooling. Own end-to-end initiatives from problem definition and data flows to dataset design, evaluation harnesses, deployment, and continuous iteration. Create robust pipelines for multi-source data to produce high-quality training/evaluation datasets, and establish feedback loops that improve models based on real member behavior.
Location: Boston
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design, build, and operate production AI systems and scaffolding around language models for WHOOP product capabilities.
  • •Lead end-to-end AI system initiatives from problem definition through data flows, dataset design, evaluation, deployment, and iteration.
  • •Build pipelines for collecting, curating, and reshaping messy, multi-source data into training and evaluation datasets.
  • •Operationalize fine-tuning and evaluation workflows, including dataset, label, and taxonomy design for member-facing features.
  • •Develop tooling and feedback loops to make experimentation and evaluation faster and to improve models continuously from real-world behavior.

Pay and Benefits

Salary: USD 150,000 - 210,000 annually
Equity and Bonus:Equity
Perks:Equity

Key Requirements

  • •3+ years of experience in applied machine learning, AI engineering, or ML-focused software engineering with significant production work.
  • •Hands-on experience building with modern language models, including prompt design, fine-tuning, and rigorous evaluation.
  • •Strong ML fundamentals across dataset construction, feature engineering, training workflows, evaluation metrics, and experiment design.
  • •Experience with LLM training and alignment techniques such as SFT, DPO, and reinforcement learning, and their impact on data and system design.
  • •Proven track record shipping and operating end-to-end ML systems, including pipelines (batch and/or streaming), inference optimization, observability, and lifecycle management.
Experience:3+ years
Skills:CommunicationCollaborationMentoringInfluencingProblem-solving
Tech Stack:Language modelsLLM observabilityFine-tuningPrompt designEvaluation harnessesExperimentation toolingDataset designSFTDPOReinforcement learningBatch pipelinesStreaming data pipelinesInference optimizationObservability

Company Brief

Whoop
Whoop designs and sells a subscription-based wearable fitness tracker and analytics platform that monitors recovery, strain, and sleep to optimize athletic performance and daily health for consumers and professional athletes.
Industry: Wearables
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: Boston, United States
Founded: 2012
WebsiteLinkedIn