AI Inference Performance Engineer - New College Grad 2026

As an AI Inference Performance Engineer, you will optimize and benchmark GenAI inference on NVIDIA's latest accelerators, define the industry's performance standards across language models, video generation, and speech workloads, and drive cross-functional execution on tight benchmark timelines.

Requirements

• BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
• 2+ years of relevant software development experience.
• Strong Python or C++ programming, software design, and software engineering skills.
• Expertise with a DL framework such as PyTorch or JAX.
• Proven track record of delivering measurable performance improvements in deep learning inference or high-performance systems.
• Deep understanding of LLM/VLM architectures and inference mechanics: attention, KV caching, batching strategies, decode-phase bottlenecks, speculative decoding, disaggregated serving etc.
• Prior experience with an LLM framework (TensorRT-LLM, vLLM, SGLang, etc) or a DL compiler in inference, deployment, algorithms, or implementation.
• Prior experience with performance modeling, profiling, debug, and code optimization of a DL/HPC/high-performance application.
• Experience with scale-out inference orchestration (MPI, NCCL, K8S) on large GPU clusters.
• Expertise in kernel development (CUTLASS, cuteDSL, tilelang, OpenAI Triton) or compiler/runtime paths (torch.compile, graph lowering, operator fusion). Architectural knowledge of CPU, GPU, FPGA or other DL accelerators; GPU programming experience (CUDA).
• Track record of leading ambiguous, high-impact technical programs across multiple teams under tight deadlines.

Benefits

• equity
• benefits