System Software Engineer, Dynamo-triton Inference Server - New College Grad 2026

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +1 · Remote

System Software Engineer role focused on developing and optimizing GPU-accelerated AI inference serving software, specifically the Dynamo-Triton Inference Server. The role involves contributing to feature development, driving customer adoption, and ensuring the platform can serve both LLM and non-LLM workloads efficiently in production environments. It requires strong C++/Rust skills, experience with distributed systems and ML systems, and a focus on optimizing throughput and latency for next-generation inference technologies.

What you'd actually do

  1. Develop world-class GPU-accelerated AI inference serving software.
  2. Contribute to feature development and drive broad customer adoption.
  3. Drive the convergence of the Triton Inference Server and NVIDIA Dynamo stacks to establish a unified, high-performance inference platform. This platform will ensure feature parity and effectively serve both Large Language Model (LLM) and non-LLM workloads.
  4. Be an active member of the open source deep learning software engineering community.
  5. Balance a variety of objectives such as building robust software designed to be deployed in production server or cloud environments, optimizing and balancing prediction throughput and latency, and developing and adopting the next generation of inference technologies.

Skills

Required

  • Rust
  • C++
  • Python
  • debugging
  • performance analysis
  • test design
  • high-scale distributed systems
  • ML systems
  • communication skills
  • agile team environment

Nice to have

  • AI frameworks and engines
  • TensorRT
  • PyTorch
  • ONNX
  • OpenVINO
  • vLLM
  • TRT-LLM
  • GPU memory management
  • cache management
  • high-performance networking
  • distributed systems programming
  • contributing to a large open source project
  • GitHub
  • bug tracking
  • branching and merging code
  • OSS licensing issues handling patches

What the JD emphasized

  • excellent Rust or C++ skills
  • strong programming & software design skills including debugging, performance analysis, and test design
  • Experience with high-scale distributed systems and ML systems

Other signals

  • GPU-accelerated AI inference serving software
  • high-performance AI inference platform
  • Triton Inference Server and NVIDIA Dynamo stacks
  • LLM and non-LLM workloads
  • production server or cloud environments
  • optimizing and balancing prediction throughput and latency
  • next generation of inference technologies