Infrastructure Engineer
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Role Details
Company: US-headquartered AI infrastructure company
Location: San Francisco, California
Employment Type: Full-time
Work Arrangement: In-office, five days per week
Experience: 5+ years in infrastructure engineering
Base Salary: $350,000–$450,000
Visa: Transfers possible
Relocation: Considered for exceptional candidates
About the Company
An innovative, venture-backed AI company building high-performance infrastructure for serving large language models (LLMs). Its platform delivers ultra-fast inference across multiple accelerator architectures and cloud environments, supporting demanding AI research and engineering workloads.
About the Role
The company is seeking a senior infrastructure engineer to own and scale its production LLM inference platform. This is a highly technical, hands-on role focused on Kubernetes, GPU infrastructure, multi-cloud deployments, and reliability for latency-sensitive AI workloads.
Responsibilities
Build and operate production Kubernetes infrastructure across AWS, GCP, and GPU cloud providers.
Optimize and troubleshoot LLM inference serving systems and GPU infrastructure.
Debug NVIDIA drivers, CUDA, NCCL, and high-performance networking issues.
Support deployments across NVIDIA GPUs and other accelerator architectures.
Build observability, automated failover, and reliability systems.
Collaborate with model optimization engineers to improve inference performance.
Own complex production issues and drive solutions independently.
Requirements
5+ years of infrastructure engineering experience, currently at Staff level or above in an IC role.
Strong production Kubernetes experience across multiple cloud environments.
Hands-on experience with production LLM inference platforms.
Expertise in NVIDIA GPU systems, CUDA, NCCL, and node-level debugging.
Experience with inference frameworks such as vLLM, SGLang, TensorRT-LLM, or Dynamo.
Knowledge of high-performance networking, such as InfiniBand, RDMA/EFA, or MPI.
Experience with observability and reliability for latency-sensitive services.
Interview Process
Initial screening call.
Technical interview.
Additional technical assessment, if required.
Final interview, potentially onsite.
🌍 Remote from anywhere in the globe
Workplace, Culture & Diversity
Corporate culture is essential to allow the organization to differentiate itself. In terms of image on the one hand, it has strengths both internally and externally to consumers. It is indeed a source of cohesion and motivation of employees and it limits conflicts. With customers, it conveys a positive image and can develop a feeling of closeness to the company or even become a criterion of choice.
About Fractal Talent
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