Staff Software Engineer, Machine Learning (Health)

Requirements

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Applied Mathematics, or a related field (Master's preferred).
• 7+ years of professional experience as a Software Engineer, Machine Learning Engineer, Platform Engineer, or related role building large-scale distributed systems and/or production ML platforms.
• Strong coding skills in Python with a track record of writing clean, well-tested, production-quality code.
• Strong fundamentals in backend and service development, including APIs, distributed systems, reliability, monitoring, debugging, and performance optimization.
• Experience designing, deploying, and operating ML inference systems at scale (real-time streaming and/or large-scale batch).
• Experience building and maintaining distributed systems, event-driven architectures, or high-throughput data processing platforms.
• Experience deploying and operating services on cloud platforms (AWS or GCP), including Kubernetes, CI/CD pipelines, infrastructure automation, and observability tooling.
• Experience partnering with data science or machine learning teams to productionize models, algorithms, and data-driven features.
• Familiarity with applied machine learning concepts, model evaluation, experimentation, and performance validation.
• Experience processing time-series, streaming, sensor, wearable, physiological, or other high-volume data sources is preferred.
• Experience developing software in a regulated or quality-managed environment (SaMD, medical device, healthcare, fintech, or similarly regulated domains) is a plus.
• 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, scalability, and/or cost at scale, while influencing cross-functional technical direction.

Additional Information

As a Staff Software Engineer on our Clinical Health team, you will design, build, and operate the production systems that deliver personalized health insights to millions of WHOOP members. You will work at the intersection of machine learning, backend engineering, cloud infrastructure, and software as a medical device (SaMD), building scalable, reliable, and observable services that power health features derived from physiological and behavioral data. In this role, you will partner closely with Applied ML Scientists, ML Research Engineers, and Digital Health teams to translate novel algorithms and research prototypes into production-grade systems. You will provide technical leadership across ML infrastructure, inference services, data pipelines, and platform architecture, ensuring our health algorithms can be deployed, monitored, validated, and operated at scale within a quality-managed environment. This role is ideal for engineers with deep experience building distributed systems and production platforms who are excited to apply those skills to machine learning-powered healthcare products.

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Company Intel

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