Principal Machine Learning Engineer

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. 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 model optimization algorithms, you will work closely with our product and research teams to develop SOTA deep learning software. You will collaborate with our technical and research teams to develop LLM training and deployment pipelines, implement model compression algorithms, and productize deep learning research. If you are someone who enjoys bridging research and production, optimizing large models, and contributing to open-source AI tooling, this role is for you.

Join us in shaping the future of AI!

Red Hat will not be providing visa sponsorship for this position. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.

What you will do

• Contribute to the design, development, and testing of various inference optimization algorithms in the , , and projects.

• Design, implement, and optimize model compression pipelines using techniques such as quantization and pruning.

• Develop and maintain speculative decoding frameworks to improve inference speed while maintaining model accuracy.

• Collaborate closely with research scientists to translate experimental ideas into robust, production-ready systems

• Profile and optimize end-to-end LLM performance, including memory usage, latency, and throughput

• Benchmark, evaluate, and implement strategies for optimal performance on target hardware

• Build tools to streamline model training, evaluation, and deployment.

• Participate in technical design discussions and propose innovative solutions to complex problems

• Contribute to open-source projects, code reviews, and documentation; collaborate with internal and external contributors.

• Mentor and guide team members, fostering a culture of continuous learning and innovation.

• Stay current with LLM architectures, inference optimizations, quantization research, and CPU/GPU hardware advancements.

What you will bring

• Strong understanding of machine learning and deep learning fundamentals with experience in one or more of LLM Inference Optimizations and NLP

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

#LI-MD2

#AI-HIRING

#vllm-1

The salary range for this position is $189,600.00 - $312,730.00. 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.

About Red Hat

is the world’s leading provider of enterprise 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. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact.

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!

Note: These benefits are only applicable to full time, permanent associates at Red Hat located in the United States.

Inclusion at Red Hat
Red Hat’s culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from different backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions that compose our global village.

Equal Opportunity Policy (EEO)
Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.

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