AI Infrastructure Engineer, Scale AI

• 4+ years of experience building large-scale, high-performance backend systems
• Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++)
• Experience with LLM serving and routing fundamentals (e.g. rate limiting, token streaming, load balancing, budgets, etc.)
• Experience with LLM capabilities and concepts such as reasoning, tool calling, prompt templates, etc
• Experience with containers and orchestration tools (e.g., Docker, Kubernetes)
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform)
• Proven ability to solve complex problems and work independently in fast-moving environments

Desirable

• As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments
• The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company
• Build and maintain fault-tolerant, high-performance systems for serving LLMs and other models at scale
• Build an internal platform to empower LLM capability discovery
• Collaborate with researchers and engineers to integrate and optimize models for production and research use cases
• Conduct architecture and design reviews to uphold best practices in system design and scalability
• Develop monitoring and observability solutions to ensure system health and performance
• Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment