Senior Principal Machine Learning Engineer

Overview

Job Summary 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 AI 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.

Job Summary 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 AI 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.

• Contribute to the design, development, and testing of various inference optimization algorithms in the vLLM and related projects, such as llm-d, LLM-compressor and speculators.
• Create and manage inference serving deployment pipelines.
• Benchmark, profile, and evaluate different parallelizations, quantization, and sparsification approaches to determine the best performance for specific hardware and models.
• Participate in technical design discussions and provide innovative solutions to complex problems.
• Stay up-to-date with the latest advancements in open source LLM model architecture, LLM inference parallelizations/optimizations techniques, and quantization research.
• Stay up-to-date with latest CPU and GPU hardware architecture and features to boost AI inference performance.
• Provide thoughtful and prompt code reviews.
• Mentor and guide other engineers and foster a culture of continuous learning and innovation.
• Collaborate with internal and external open source committers and contributors while contributing to vLLM and related projects.

• Strong understanding of machine learning and deep learning fundamentals with experience in one or more of LLM Inference Optimizations, Computer Vision, NLP, and reinforcement learning.
• Experience with tensor math libraries such as PyTorch and Num Py.
• Strong programming skills with proven experience implementing Python based machine learning solutions.
• Ability to develop and implement research ideas and algorithms.
• Experience with mathematical software, especially linear algebra.
• Understanding of Linear Algebra, Gradients, Probability, and Graph Theory.
• 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 strong plus.

The salary range for this position is $ - $. Actual offer will be based on your qualifications.

Pay Transparency Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat’s compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience.

Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure.

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