Role overview
At Red Hat we believe the future of AI is open and we are on a mission to bring the power of open-source LLMs and vLLM to every enterprise. Red Hat Inference team accelerates AI for the enterprise and brings operational simplicity to GenAI deployments. As leading developers, maintainers of the vLLM project, and inventors of state-of-the-art techniques for model quantization and sparsification, our team provides a stable platform for enterprises to build, optimize, and scale LLM deployments.
As a Machine Learning Engineer focused on vLLM, you will be at the forefront of innovation, collaborating with our team to tackle the most pressing challenges in model performance and efficiency. Your work with machine learning and high performance computing will directly impact the development of our cutting-edge software platform, helping to shape the future of AI deployment and utilization. If you are someone who wants to contribute to solving challenging technical problems at the forefront of deep learning in the open source way, this is the role for you.
Join us in shaping the future of AI!
What you'll work on
- Write robust Python and C++, working on vLLM systems, high performance machine learning primitives, performance analysis and modeling, and numerical methods
- Contribute to the design, development, and testing of various inference optimization algorithms
- Participate in technical design discussions and provide innovative solutions to complex problems
- Give thoughtful and prompt code reviews. Proactively utilizing AI-assisted development tools for code generation, auto-completion, and intelligent suggestions to accelerate development cycles and enhance code quality.
- Mentor and guide other engineers and foster a culture of continuous learning and innovation
- Extensive experience in writing high performance code for GPUs and deep knowledge of GPU hardware
- Strong understanding of computer architecture, parallel processing, and distributed computing concepts
- Experience with tensor math libraries such as PyTorch
- Modern C++, CUDA, Triton, and CUTLASS experience
- Mathematical software, especially linear algebra or signal processing
- Experience optimizing kernels for deep neural networks
- Experience with NVIDIA Nsight is a plus
- Strong communications skills with both technical and non-technical team members
- BS, or MS in computer science or computer engineering or a related field. A PhD in a ML related domain is considered a plus