Red Hat · 16 hours ago
Machine Learning Systems Research Intern, PhD, Summer 2026
Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing technologies. They are seeking a highly motivated summer intern to join their Machine Learning Research Team, where the intern will work on AI inference and model optimization techniques.
Enterprise SoftwareInsurTechLinuxOpen SourceOperating SystemsSoftware
Responsibilities
Research and implement techniques for LLM inference and LLM optimizations
Conduct experiments to evaluate the impact of optimization methods on model accuracy, latency, and throughput
Collaborate with researchers and engineers to integrate optimizations into real-world machine learning workflows
Document findings and contribute to technical reports, blog posts, or research publications
Qualification
Required
Currently pursuing a Ph.D. degree in Computer Science, Electrical Engineering, Machine Learning, or a related field
Strong programming skills in C++, CUDA, and Python
Experience with tensor math libraries such as PyTorch
Familiarity with AI model optimization techniques such as quantization (e.g., INT4, FP8), pruning, and knowledge distillation
Deep understanding and experience in GPU performance optimizations
Excellent knowledge of large language model architectures
Strong analytical and problem-solving skills
Excellent communication skills and ability to work in a team-oriented research environment
Preferred
Background in efficient inference techniques for large-scale language models or computer vision models
Prior experience contributing to open-source ML frameworks or research publications
1 or more co-authored papers at a top tier conference like NeurIPS, ICLR, ACL, CVPR, MLSys is a big plus
Benefits
Competitive stipend and potential for full-time opportunities.
Company
Red Hat
Red Hat is a software company that offers enterprise open-source software solutions. It is a sub-organization of IBM.
H1B Sponsorship
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2025 (159)
2024 (148)
2023 (156)
2022 (181)
2021 (154)
2020 (106)
Funding
Current Stage
Public CompanyTotal Funding
unknown2018-10-28Acquired
1999-08-20IPO
1999-03-09Corporate Round
Leadership Team
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