Senior AI Infrastructure Engineer

📋 Description

• Build and own model-serving infrastructure.
• Manage GPU clusters and workload scheduling.
• Improve inference performance.
• Support distributed training and model iteration.
• Make deployments observable and incidents traceable.
• Own production reliability.

🎯 Requirements

• Hands-on AI infrastructure experience with at least 1 year building and operating infrastructure
• Production model deployment experience with engines such as vLLM, SGLang, TensorRT-LLM, Triton
• GPU cluster and orchestration experience using Kubernetes, Slurm, or an equivalent platform
• Performance debugging skills using traces, metrics, and profiling tools
• Proficient in Python and comfortable with backend or systems development in Go, C++, Rust, or a
• Practical experience with Linux, containers, deployment automation, and distributed services

🎁 Benefits

• $1,000 annual learning and development budget
• $150/month health and wellness allowance
• $500 home office budget
• 26 weeks paid primary parental leave
• 18 weeks paid secondary parental leave
• Fertility support up to $10,000