Senior Machine Learning Engineer, Insights

Whoop!

Senior Machine Learning Engineer developing and deploying ML systems for health insights at WHOOP. Collaborating with data scientists and researchers to enhance health metrics for members.

Posted 7/7/2026full-timeBoston • Massachusetts • 🇺🇸 United StatesSenior💰 $150,000 - $210,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and maintaining production ML systems, with strong coding skills in Python and experience in deploying ML inference systems on cloud platforms. Collaborates effectively with cross-functional teams to ensure model performance and alignment with physiological insights.

Highest-signal resume keywords

Python ProgrammingML System DeploymentCloud Platforms (AWS, GCP)Backend/Service DevelopmentCI/CD Practices

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine Learning EngineeringProduction-Quality CodeAPIs DevelopmentMonitoring and DebuggingStatistical TechniquesTime Series Data AnalysisML FrameworksPerformance Validation

Soft Skills

CollaborationProblem-Solving

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree Preferred

Industry Keywords

Data ScienceMLOpsPhysiological InsightsModel PerformanceData Pipelines

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

Create, improve, and maintain production services that provide analysis for health features in collaboration with data scientists and MLOps engineers
Collaborate with data engineers to improve ML data pipelines, tooling, and validation systems that support robust model performance
Work alongside data scientists to translate research prototypes into production ML systems optimized for scale, latency and cost efficiency
Collaborate with researchers and product teams to align model development with physiological insights and member impact
Participate in on-call rotations for data science services, ensuring uptime and performance in production environments

Requirements

What you’ll need

Bachelor's Degree in Computer Science, Data Science, Applied Mathematics, or a related field (Master’s preferred).
4+ years of professional experience as a ML engineer, applied researcher, or software engineer with a focus on ML systems
Strong coding skills in Python with a track record of writing clean, production-quality code
Experience designing, deploying and operating ML inference systems at scale (real-time streaming and/or large-scale batch)
Strong fundamentals in backend/service development (APIs, reliability, monitoring, debugging) as it relates to serving ML models
Experience deploying and maintaining ML systems on cloud platforms (AWS or GCP), including CI/CD and observability practices
Familiarity with applied ML development (frameworks, evaluation criteria, performance validation) and translating prototypes into production systems
Preferred: 2+ years of experience applying advanced mathematical and statistical techniques
Preferred: Experience working with time series data (wearable, physiological, or high-frequency sensor data)

Benefits

Comp & perks

Generous equity package
Benefits including health insurance