AI Infrastructure Engineer
U
UtilidataAI, Energy Infrastructure
This position can be performed remotely from anywhere in the United States.Full-TimeSenior
Salary$170,000 to $210,000 base compensation
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Job Details
- Experience
- 5+ years
- Required Skills
- DockerPythonKubernetesCI/CDMLOpsDistributed Systems
Requirements
- 5+ years of software engineering experience with a strong focus on AI infrastructure, backend systems, or distributed systems
- Hands-on experience with AI model serving frameworks such as vLLM, SGLang, Triton, TensorRT, or TorchServe
- Understanding of container orchestration and cluster management tools like Kubernetes and Docker
- Experience deploying and operating infrastructure across both datacenter and on-prem environments
- Strong knowledge of GPU workloads and the differences between inference and training
- Proficiency in Python
- Excellent communication skills and ability to work cross-functionally
- Willingness to travel up to 10% of time
Responsibilities
- Lead the design and build of Utilidata's AI inference platform
- Own end-to-end model serving infrastructure for on-prem and datacenter environments
- Build and maintain fault-tolerant, high-performance systems for serving AI models at scale
- Collaborate with algorithms engineers to integrate AI inference data and configuration
- Optimize GPU utilization and inference performance across hardware fleets
- Establish MLOps best practices including CI/CD pipelines
- Contribute to infrastructure roadmap decisions and tooling selection
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