Infrastructure Engineer focused on MLOps for AI/ML platform at Raw Power Labs. Designing and maintaining infrastructure for model training, inference, and deployment systems.
Responsibilities
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.
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