AI Inference Engineer

Premier Global Links LLCPalo Alto, CA
$230,000 - $350,000Onsite

About The Position

Premier Global Links LLC is seeking an experienced Member of Technical Staff, Inference Systems, to build and optimize a high-performance AI inference platform from the ground up. This role is focused on LLM inference, model serving, distributed systems, and inference runtime performance. The ideal candidate has hands-on experience with production inference systems and strong systems engineering skills, with Rust experience highly valued.

Requirements

  • 2–10 years of experience in backend, distributed systems, or systems engineering.
  • Hands-on experience building, operating, or optimizing LLM inference or serving systems.
  • Deep understanding of transformer inference internals, including attention, KV cache, batching, and scheduling.
  • Experience with a production inference engine such as vLLM, SGLang, or TensorRT-LLM.
  • Strong programming experience with Rust, C++, Go, or systems-level Python/PyTorch.
  • Experience building performance-critical systems where latency, throughput, and cost are important.
  • Strong distributed systems and production software engineering fundamentals.
  • Ability to work on-site 5 days per week in Palo Alto, CA.

Nice To Haves

  • Production Rust experience.
  • CUDA or Triton kernel development experience.
  • Multi-GPU or multi-node serving experience.
  • Experience with NCCL, NVLink, or RDMA.
  • Experience with prefix caching, speculative decoding, or prefill/decode disaggregation.
  • Contributions to open-source inference projects such as vLLM, SGLang, or Dynamo.
  • Experience working on inference systems at an AI provider, accelerator company, research lab, or similar organization.
  • Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related technical field.

Responsibilities

  • Build and optimize production LLM inference and model-serving systems.
  • Develop inference runtime components using Rust and other systems-level technologies.
  • Design and implement batching, scheduling, request routing, and serving infrastructure.
  • Build and optimize KV cache and prefix caching systems.
  • Scale inference workloads across multi-GPU and multi-node environments.
  • Profile, benchmark, and optimize latency, throughput, reliability, and cost.
  • Work with inference engines such as vLLM, SGLang, or TensorRT-LLM.
  • Investigate performance bottlenecks across the inference stack.
  • Contribute to core architecture and technical decisions for the platform.
  • Collaborate with a small, hands-on engineering team in a fast-paced environment.

Benefits

  • $230,000–$350,000 annual salary, based on experience and qualifications.
  • Equity opportunity starting at approximately 0.5%, with flexibility based on experience.
  • Professional growth and development opportunities.
  • High-impact work within a fast-paced AI technology environment.
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