# Senior Machine Learning Engineer, Insights

**Company:** [WHOOP](https://hotfix.jobs/companies/whoop)
**Location:** Boston, MA
**Role:** ML Engineering
**Experience:** 4+ years
**Skills:** Python, Machine Learning, Ml Inference Systems, AWS, GCP, CI/CD, Time Series Data, APIs, Backend Development, MLOps
**Posted:** 2026-07-07

> Senior Machine Learning Engineer building and deploying scalable production ML systems for personalized health insights from wearable physiological data. Requires 4+ years ML engineering experience, strong Python and backend skills, and experience with inference at scale.

## Job Description

## Responsibilities
- 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.

## Qualifications
- 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.
- Experience working with time series data (wearable, physiological, or high-frequency sensor data).

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