What you'll be doing:
Craft and develop robust inference software that can be scaled to multiple platforms for functionality and performance.
Performance analysis, optimization, and tuning for Large Language Models (LLMs)
Conduct unit tests and performance tests for different stages of the inference pipeline.
Closely follow academic developments in the field of artificial intelligence and feature update TensorRT-LLM.
Write safe, scalable, modular, and high-quality (C++/Python) code for our core backend software for LLM inference.
Collaborate across the company to guide the direction of deep learning inference, working with software, research and product teams.
What we need to see:
Bachelors, Masters or higher degree in Computer Engineering, Computer Science, Applied Mathematics or related computing focused degree (or equivalent experience).
5+ years of relevant software development experience.
Excellent Python programming skills, software design, and software engineering skills.
Awareness of the latest developments in LLM architectures and LLM inference techniques.
Experience working with deep learning frameworks like PyTorch and HuggingFace.
Proactive and able to work without supervision.
Excellent written and oral communication skills in English.
Ways to stand out from the crowd:
Prior experience with a LLM inference framework (TensorRT-LLM, SGLang, vLLM, 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.
Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.
Architectural knowledge of CPU and GPU.
GPU programming experience (CUDA or OpenCL).
