Senior Software Engineer - vLLM Inference

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 compression, our team provides a stable platform for enterprises to build, optimize, and scale LLM deployments.

We are seeking an experienced Senior ML Ops engineer to work closely with our product and research teams to scale SOTA deep learning products and software. As an ML Ops engineer, you will work closely with our technical and research teams to manage training and deployment pipelines, create DevOps and CI/CD infrastructure, and scale our current technology stack. If you are someone who wants to contribute to solving challenging technical problems at the forefront of deep learning, this is the role for you! You would be joining the core team behind 2025's most popular open source project on Github.

In this role, your primary responsibility will be to build and release the Red Hat AI Inference runtimes, continuously improve the processes and tooling used by the DevOps team, and find opportunities to automate procedures and tasks.

Join us in shaping the future of AI!

What you will do

• Collaborate with research and product development teams to scale machine learning products for internal and external applications

• Create and manage model training and deployment pipelines

• Actively contribute to managing and releasing upstream and midstream product builds

• Test to ensure correctness, responsiveness, and efficiency

• Troubleshoot, debug and upgrade Dev & Test pipelines

• Identifying and deploying cybersecurity measures by continuously performing vulnerability assessment and risk management

• Collaborate with a cross-functional team about market requirements and best practices

• Keep abreast of the latest technologies and standards in the field

What you will bring

• 2+ years of experience in MLOps, DevOps, Automation and modern Software Deployment practices

• Experience evaluating LLMs for performance on accelerators and accuracy (think HellaSwag, MMLU, Chatbot Arena, TruthfulQA, etc.).

•  Being super comfortable with Python and PyTest is a must.

• Strong experience with Git, Github Actions including self-hosted runners, Terraform, Jenkins, Ansible, and common technologies for automation and monitoring

• Highly experienced with administering Kubernetes/Openshift

• Familiar with Agile development methodology 

• Experience with Cloud Computing using at least one of the following Cloud infrastructures: AWS, GCP, Azure, or IBM Cloud

• Solid programming skills especially in Python

• Solid troubleshooting skills

• Ability to interact comfortably with the other members of a large, geographically dispersed team 

• Experience maintaining an infrastructure and ensuring stability 

• While a Bachelor’s degree or higher in computer science, mathematics, or a related discipline is valued, we prioritize technical prowess, initiative, problem solving, and practical experience

Following is considered a plus

• Familiarity with contributing to the vLLM CI community is a big plus

#LI-MD2

#AI-HIRING

The salary range for this position is $133,650.00 - $220,680.00. 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-p