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 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.You would be joining the core team behind 2025's most popular open source project on Github.
As a Machine Learning Engineer focused on distributed vLLM infrastructure, you will collaborate with our team to tackle the most pressing challenges in scalable inference systems and Kubernetes-native deployments. Your work with distributed systems and cloud infrastructure will directly impact enterprise AI deployments. If you want to solve challenging technical problems in distributed systems and cloud-native infrastructure the open-source way, this is the role for you.
Join us in shaping the future of AI!
Build and maintain distributed inference infrastructure using Kubernetes APIs, operators, and the Gateway Inference Extension API for scalable LLM deployments
Develop systems components in Go and/or Rust to integrate with the vLLM project and manage distributed inference workloads
Design and implement KV cache aware routing and scoring algorithms to optimize memory utilization and request distribution across large scale inference deployments
Improve the resource utilization, fault tolerance, and stability of the inference stack
Contribute to the design, development, and testing of various inference optimization algorithms
Participate in technical design discussions and provide innovative solutions to complex problems
Give thoughtful and prompt code reviews
Mentor and guide other engineers and foster a culture of continuous learning and innovation
Strong proficiency in Python and one or more system programming languages (Golang, Rust, C++)
Strong understanding of computer architecture, parallel processing, and distributed computing concepts
Experience with the Kubernetes ecosystem, including custom APIs, operators, and the Gateway API inference extension for GenAI workloads (nice to have)
Experience with cloud native Kubernetes service mesh technologies/stacks like Istio, Cillium, Envoy (WASM filters) and CNI
Experience with tensor math libraries such as PyTorch
Working understanding of high-performance networking protocols and technologies including UCX, RoCE, InfiniBand, and RDMA
Mathematical software, especially linear algebra or signal processing
Deep understanding and experience in GPU performance optimizations
Experience optimizing kernels for deep neural networks
Experience with profiling tools like NVIDIA Nsight or distributed tracing libraries/techniques like OpenTelemetry is a plus
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 plus
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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
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.
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.