Senior engineer responsible for architecting and scaling Pfizer’s AI infrastructure. Collaborating on cloud engineering, DevOps, and MLOps for biotech and healthcare solutions.
About the role
- Design and implement scalable ML training and inference pipelines using AWS container orchestration.
- Architect and manage containerized workloads for AI model training, conversion, and deployment.
- Optimize cost and performance of GPU-accelerated compute infrastructure.
- Build robust monitoring, logging, and alerting systems for production ML workloads.
- Drive ML infrastructure strategy and best practices across the organization.
- Maintain and extend our C#/.NET backend APIs and microservices architecture.
- Collaborate on feature development and technical architecture decisions.
Requirements
- 5+ years in DevOps, Platform Engineering, or MLOps with deep AWS ecosystem experience.
- Experience with C#/.NET development and modern backend practices.
- Proven expertise with containerization, infrastructure as code, and CI/CD systems.
- Deep understanding of ML/AI workloads, model deployment, and production ML systems.
- Experience with microservices architecture, APIs, and database management.
Benefits
- Competitive salaries.
- Supplemental pension contributions.
- 30 days of annual vacation.
- Flexible work hours, remote when you need to.
- Great focus on work/life balance.
- Bleeding edge tech stack.
- Skilled co-workers who are driven by a passion for creating beautiful games and cool tech.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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