AI Infrastructure Engineer IV (Lehi)

Title: AI Infrastructure Engineer IV
Location : Salt Lake City region
Target Start Date : ASAP
Type: Contract-to-Hire (Direct Hire possible)
Pay Rate: $72.00-$85.00/hr ($150K-$175K)

Overview
Our client, a leader and growing presence in the robotics and autonomous vehicles space, is seeking a senior-level AI Infrastructure Engineer to architect and operate the high-performance computing environments that power advanced autonomous and AI systems. This role designs and scales GPU-accelerated, cloud, and distributed platforms that support AI research, model training, and production deployment.
You will partner with AI researchers, robotics engineers, and software teams to build reliable, secure, and high-throughput infrastructure that enables rapid experimentation and dependable field deployment.

• Design and maintain high-performance compute, GPU, storage, and networking infrastructure for AI/ML workloads
• Build and operate cloud environments (AWS, Azure, GCP) optimized for scalability, performance, and cost efficiency
• Implement automation, CI/CD, DevOps, and MLOps pipelines for AI development and deployment
• Optimize compute and storage systems for throughput, latency, and reliability
• Monitor system health, capacity, and performance while resolving infrastructure bottlenecks
• Support model training, experimentation, and production deployment workflows
• Partner cross-functionally with AI, robotics, and software engineering teams

• Bachelor's degree in Computer Science, Engineering, or related field
• 10+ years in cloud, platform, or DevOps engineering
• 2+ years supporting AI/ML environments
• Strong proficiency in Python
• Experience with GPU-accelerated and distributed compute systems
• Hands-on experience with AWS, Azure, or GCP
• Experience with Kubernetes, Docker, Terraform, or similar orchestration tools
• Familiarity with PyTorch, TensorFlow, or comparable ML frameworks
• Strong troubleshooting, automation, and performance optimization skills

• Experience supporting autonomy, robotics, or embedded AI systems
• Background in large-scale storage, high-throughput networking, or on-prem + hybrid cloud architectures

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