5 ai ml infrastructure engineer jobs at 5 companies in Sun City, CA
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Staff AI Infrastructure Engineer -
Costa Mesa or Seattle or Washington or Boston
$220k-$292k/yrOnsiteFull Time
Anduril Industries: Defense technology building autonomous military hardware and software.
7+ YOERequires 7+ years building production-scale ML systems, proficiency in Python, Go, or C++, distributed systems expertise, Docker/Kubernetes, distributed training, data pipelines, technical leadership, and Top Secret clearance eligibility.
Cloud Infrastructure & AI Operations Engineer (On-Site Only)
Santa Ana, California, United States
$95k-$125k/yrOnsiteFull Time
Pioneer Circuits: A manufacturer of high-performance flexible printed circuit boards serving aerospace, defense, and advanced technology customers.
Hands-on AWS experience, infrastructure as code (Terraform/CloudFormation/CDK), CI/CD (GitLab CI), scripting (Python/Bash/PowerShell), containerization (Docker), observability, and experience deploying AI/ML workloads in regulated environments; must be U.S. citizen or lawful permanent resident.
Phoenix or San Diego or San Francisco or Los Angeles or Denver or Portland or Seattle
$185k-$235k/yrOnsiteFull Time
World Wide Technology: Global technology solutions provider and systems integrator.
10+ YOEMinimum 10 years in technical pre-sales or solutions architecture; hands-on AI/ML infrastructure design experience; ability to whiteboard end-to-end AI architectures; bachelor’s degree required; experience with NVIDIA systems and public cloud platforms.
NVIDIA DGX/HGX, CUDA, AI Enterprise, NeMo, Omniverse, NVAIE, AWS, Azure, GCP, Dell, HPE, Cisco, NetApp, Pure Storage, Vast Data
Irvine or Denver or Indianapolis or Grand Rapids or Lexington or Los Angeles or Louisville or Texas or San Francisco or United States
$218k-$225k/yrOnsiteFull Time
Trace3: Provides IT consulting and technology solutions for enterprise digital transformation.
12+ YOE5+ MgmtBachelor's in CS/EE or related; 12+ years enterprise infrastructure experience with 5+ years designing and implementing production-scale AI/ML/HPC (multi-rack GPU) and 5+ years people leadership; familiarity with GPU compute, high-performance networking, scale-out storage, Kubernetes/Slurm/Run:ai, and AI security; willingness to travel up to 50%.