
Staff Software Engineer, Machine Learning (Health)
Job Description
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.
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.