Senior Cloud Engineer, ML Platform

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Requirements:

• 4+ years of hands-on cloud engineering experience with a focus on scaling ML/AI infrastructure in high-throughput, real-time environments.
• Proficiency in Infrastructure-as-Code (Terraform, CloudFormation, or equivalent) to automate cloud infrastructure for ML systems.
• Deep knowledge of AWS services, patterns and best practices for resiliency, scalability, and security.
• Hands-on experience with container orchestration (e.g., Kubernetes, ECS) with a focus on solving real-world scalability challenges.

Responsibilities:

• Architect and scale cloud-based infrastructure purpose-built for real-time and batch ML workloads, ensuring system efficiency and reliability.
• Design model-serving infrastructure to handle high-throughput inference workloads, model versioning, and multi-model interactions.
• Design observability strategies, ensuring model performance, system reliability, and infrastructure health are continuously monitored.
• Collaborate with ML/DevOps/Backend/Security Engineers on projects, integrating new tools, improving deployment speeds, scalability, and resiliency to support their evolving roadmaps.