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Red Hat

Senior Machine Learning Engineer

Red Hat

Machine Learning Engineer at Red Hat focused on optimizing AI models and contributing to open-source AI tooling. Collaborating on model compression algorithms and deploying deep learning research solutions.

Posted 6/2/2026full-timeToronto • 🇨🇦 CanadaSeniorWebsite

Tech Stack

Tools & technologies
NumpyPythonPyTorch

About the role

Key responsibilities & impact
  • Contribute to the design, development, and testing of various inference optimization algorithms
  • Design, implement, and optimize model compression pipelines
  • Develop and maintain speculative decoding frameworks
  • Collaborate closely with research scientists to translate experimental ideas into robust, production-ready systems
  • Profile and optimize end-to-end LLM performance
  • 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
  • Contribute to open-source projects, code reviews, and documentation
  • Mentor and guide team members, fostering a culture of continuous learning and innovation
  • Stay current with LLM architectures, inference optimizations, and hardware advancements.

Requirements

What you’ll need
  • Strong understanding of machine learning and deep learning fundamentals
  • Experience in 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.

Benefits

Comp & perks
  • Health insurance
  • Flexible working hours
  • Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools
inference optimization algorithmsmodel compression pipelinesspeculative decoding frameworksLLM performance optimizationtensor math librariesPython programminglinear algebragradientsprobabilitygraph theory
Soft Skills
collaborationmentoringcommunicationinnovationcontinuous learning
Certifications
BS in computer scienceMS in computer sciencePhD in ML related domain