# Staff Machine Learning Engineer (Health)

**Company:** [WHOOP](https://hotfix.jobs/companies/whoop)
**Location:** Boston, MA
**Role:** ML Engineering
**Experience:** 7+ years
**Skills:** Python, Machine Learning, Time Series Data, Ml Inference, AWS, GCP, CI/CD, Backend Development, APIs, Data Pipelines
**Posted:** 2026-05-04

> Designs, builds, and productionizes ML systems for personalized health insights from physiological data in a regulated SaMD environment. Collaborates with scientists, data platforms, and health teams; requires 7+ years experience, Python expertise, and cloud deployment skills.

## Job Description

## Responsibilities

- Design, build, and maintain production services that deliver health features, in close collaboration with Applied ML Scientists and ML Research Engineers.
- Collaborate with Data Platform teams to improve ML data pipelines, tooling, and validation systems that support robust model performance.
- Work alongside Applied ML Scientists to translate research prototypes into production ML systems optimized for scale, latency, and cost efficiency.
- Partner with the Digital Health team on algorithmic performance specifications, validation and verification planning, and the design of SPA or algorithm validation studies.
- Collaborate with researchers and product teams to align model development with health 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**).
- **7+ years** of professional experience as a Machine Learning Engineer or Software Engineer building production ML systems.
- Proven experience working with **time series data** (wearable, physiological, or high-frequency sensor data preferred).
- Experience designing, deploying, and operating **ML inference systems** at scale (real-time streaming and/or large-scale batch).
- Strong coding skills in **Python** with a track record of writing clean, well-tested, production-quality code.
- 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.
- Experience developing ML-enabled software in a regulated or quality-managed environment (SaMD or medical device), with working knowledge of change control, quality documentation, traceability, and verification/validation practices.
- Demonstrated technical leadership through architecture and design ownership, setting engineering standards, and raising quality through reviews and mentorship.
- Proven track record driving measurable improvements in system performance, reliability, and/or cost at scale, and influencing cross-functional technical direction.

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