Senior Machine Learning Engineer

Red Hat • Boston, MA

1d • Remote

About The Position

At Red Hat, we are dedicated to advancing the future of AI through open-source solutions, specifically focusing on bringing the power of open-source LLMs and vLLM to enterprises. Our AI Inference team is at the forefront of accelerating AI for businesses and simplifying the operational aspects of GenAI deployments. As key developers and maintainers of the vLLM project, and innovators in model quantization and sparsification techniques, we provide a robust platform for enterprises to build, optimize, and scale their LLM deployments. In this role as a Senior Principal Machine Learning Engineer specializing in model optimization algorithms, you will collaborate closely with our product and research teams to develop state-of-the-art deep learning software. Your responsibilities will include developing LLM training and deployment pipelines, implementing model compression algorithms, and productizing deep learning research in collaboration with our technical and research teams. This is an opportunity to contribute to solving complex technical challenges at the cutting edge of deep learning within an open-source framework. Join us in shaping 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 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 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