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Senior Machine Learning Engineer

Red Hat, Inc. -
Toronto, ON

Apply Now

Job details

Full-time

Qualifications

Law
Doctoral degree
Computer Science
Kubernetes
PyTorch
Engineering
NumPy
Research
Master's degree
Math
Bachelor's
Machine learning
Computer Engineering
Natural language processing
Linux
Model evaluation
Python

Full job description

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.

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 LLM-compressor, Speculators, and vLLM 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

About Red Hat

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. 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.

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.

Red Hat does not seek or accept unsolicited resumes or CVs from recruitment agencies. We are not responsible for, and will not pay, any fees, commissions, or any other payment related to unsolicited resumes or CVs except as required in a written contract between Red Hat and the recruitment agency or party requesting payment of a fee.

Red Hat supports individuals with disabilities and provides reasonable accommodations to job applicants. If you need assistance completing our online job application, email [email protected]. General inquiries, such as those regarding the status of a job application, will not receive a reply.

Apply Now

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Senior Machine Learning Engineer

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What you will bring

Red Hat supports individuals with disabilities and provides reasonable accommodations to job applicants. If you need assistance completing our online job application, email [email protected]. General inquiries, such as those regarding the status of a job application, will not receive a reply.

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