Machine Learning Infrastructure Engineer

Job summary

Seeking a Machine Learning Infrastructure Engineer to design, build, and operate high-performance inference platforms for large machine learning models in production.

Qualifications

• Six or more years of experience in distributed systems, infrastructure, or ML platform engineering
• Strong proficiency in Python and a systems language such as Go, Rust, or C++
• Deep experience operating high-throughput, low-latency services in production
• Hands-on experience with LLM or large model inference frameworks such as vLLM or TensorRT-LLM
• Strong understanding of GPU architecture, memory hierarchies, and accelerator utilization
• Familiarity with Kubernetes, autoscaling, and modern cloud platforms
• Experience with observability stacks including metrics, tracing, and structured logging
• Solid grounding in performance engineering and capacity planning
• Strong communication and incident response skills

Responsibilities

• design, build, and operate high-performance inference platforms for large machine learning models
• focus on systems engineering for AI deployment, including request routing, batching, caching, autoscaling, GPU utilization, and observability

Skills

Degrees

Relocation