about 6 hours ago
Responsibilities
- Design, build, and maintain production services for health features.
- Lead the architecture and development of scalable ML inference systems and APIs.
- Collaborate with Data Platform teams to enhance ML data pipelines and validation frameworks.
- Translate research prototypes into deployable production systems.
- Partner with the Digital Health team on algorithm validation and performance specifications.
- Drive operational excellence through monitoring and reliability improvements.
- Align platform investments with health insights and member impact.
- Participate in on-call rotations for ML and data services.
- Provide technical leadership through architecture reviews and mentorship.
Requirements
- Bachelor's degree in Computer Science, Software Engineering, or related field; Master's preferred.
- 7+ years of experience in software engineering or related roles.
- Strong coding skills in Python with a focus on production-quality code.
- Fundamentals in backend development, APIs, and distributed systems.
- Experience with ML inference systems at scale.
- Experience with cloud platforms like AWS or GCP, including Kubernetes.
- Experience partnering with data science teams to productionize models.
- Familiarity with applied machine learning concepts and model evaluation.
- Preferred experience with time-series and high-volume data processing.
- Experience in regulated environments like healthcare or fintech is a plus.
- Demonstrated technical leadership and influence on system performance.