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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer (Data Science Algorithms) - **Company:** Whoop, Inc. - **Location:** Boston, MA, United States - **Experience:** Expert - **Salary:** $150,000.0 - $210,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Cloud Computing, Continuous Integration, Software Debugging, Python (Programming Language), Machine Learning, Service Development Studio, Data Streaming, Google Cloud, Performance Testing, Backend, Information Technology, Production Code, Machine Learning Operations, Software Coding, Data Pipelines - **Published:** June 24, 2026 - **Apply:** https://www.dice.com/job-detail/19fe6121-44fb-4478-be3c-8bcf8e524620 ## About the Role * 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 Google Cloud Platform), 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) This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office. ## Description WHOOP is an advanced health and fitness wearable, on a mission to unlock human performance. WHOOP empowers its members to improve their health and perform at a higher level by providing a deep understanding of their bodies and daily lives. Our data science algorithms teams are responsible for developing novel algorithms and features that expand our health and fitness capabilities with medical-grade metrics. We combine continuous physiological data with clinical research and expert knowledge to generate features that are both scientifically grounded and deeply impactful for members. Currently, we have two Senior MLE roles open across two teams: DS Health team: novel algorithms within the domains of women's health, multimodal longitudinal health insights, and SaMD DS Core Algos team: performance-related insights for sleep, recovery, or exercise As a Senior Machine Learning Engineer on our Core Algos or Health team, you will design, build, and productionize ML systems that deliver meaningful, personalized health metrics to millions of members. You will work at the intersection of data science, backend engineer, and cloud infrastructure - deploying robust, scalable, and reliable ML solutions build on physiological and behavioral data streams. This role emphasizes strong coding skills, system design, and ability to deliver production-ready ML systems., * 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 ## Related Videos - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [The Cloud is Calling: Answer with In-Demand Skills](https://www.wearedevelopers.com/videos/945-the-cloud-is-calling-answer-with-in-demand-skills) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)