about 4 hours ago
Responsibilities
- Design, build, and maintain production services for health features.
- Collaborate with Data Platform teams to enhance ML data pipelines and validation systems.
- Translate research prototypes into production ML systems optimized for scale and efficiency.
- Partner with the Digital Health team on algorithm validation and performance specifications.
- Align model development with health insights and member impact through collaboration with researchers and product teams.
- Participate in on-call rotations for data science services.
Requirements
- Bachelor's degree in Computer Science, Data Science, Applied Mathematics, or related field; Master's preferred.
- 7+ years of experience as a Machine Learning Engineer or Software Engineer in production ML systems.
- Proven experience with time series data, preferably from wearables or sensors.
- Experience in designing and operating ML inference systems at scale.
- Strong coding skills in Python with a focus on clean, production-quality code.
- Experience deploying ML systems on cloud platforms like AWS or GCP, including CI/CD practices.
- Familiarity with applied ML development and translating prototypes into production systems.
- Experience in regulated environments, with knowledge of quality documentation and validation practices.
- Demonstrated technical leadership in architecture and design ownership.
- Proven track record of improving system performance and influencing technical direction.