Senior Principal Machine Learning Engineer, vLLM

Red River • Boston, MA

3d • Remote

About The Position

At Red Hat, we are committed to advancing the future of AI through open source, aiming to bring the power of open-source LLMs and vLLM to every enterprise. Our AI Inference team focuses on accelerating AI for businesses and simplifying GenAI deployments. As key contributors to the vLLM project and pioneers in model quantization and sparsification techniques, we provide a robust platform for enterprises to build, optimize, and scale their LLM deployments. In this role, you will focus on model optimization algorithms, working closely with our product and research teams to develop state-of-the-art deep learning software. You will collaborate with technical and research teams to create LLM training and deployment pipelines, implement model compression algorithms, and bring deep learning research into production. This is an opportunity to tackle challenging technical problems at the forefront of deep learning within an open-source framework and shape the future of AI.

Requirements

• 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 NumPy.
• 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.

Nice To Haves

• A PhD in a ML related domain is considered a strong plus.

Responsibilities

• Contribute to the design, development, and testing of various inference optimization algorithms in 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 the open source LLM model architecture, LLM Inference parallelizations/optimizations techniques, and quantization research.
• Stay up-to-date of latest CPU and GPU hardware architecture and features to boost AI inference performance.
• Give thoughtful and prompt code reviews.
• Mentor and guide other engineers and foster a culture of continuous learning and innovation.
• Continuous collaboration with internal and external open source committers and contributors while contributing to vLLM and related projects.

Benefits

• Comprehensive medical, dental, and vision coverage
• Flexible Spending Account - healthcare and dependent care
• Health Savings Account - high deductible medical plan
• Retirement 401(k) with employer match
• Paid time off and holidays
• Paid parental leave plans for all new parents
• Leave benefits including disability, paid family medical leave, and paid military leave
• Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more!

What This Job Offers

• Job Type: Full-time
• Career Level: Senior