Principal Machine Learning Engineer

Red Hat

Machine Learning Engineer optimizing model compression and LLM performance at Red Hat. Collaborating closely with research teams and contributing to open-source AI developments.

Posted 6/2/2026full-timeBoston • Massachusetts • 🇺🇸 United StatesLead💰 $189,600 - $312,730 per yearWebsite

Tech Stack

Tools & technologies

NumpyPythonPyTorch

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

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!

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

inference optimization algorithmsmodel compressionquantizationpruningspeculative decodingLLM performance profilingbenchmarkingPythontensor math librarieslinear algebra

Soft Skills

collaborationmentoringcommunicationproblem-solvinginnovationcontinuous learning

Certifications

BS in computer scienceMS in computer sciencePhD in ML related domain