Senior Manager, AI Inference
Red HatBoston$211k – $358kPosted 31 March 2026
Job Description
About the Job
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 engineering team accelerates AI for the enterprise and brings operational simplicity to GenAI deployments. As leading maintainers of the vLLM and LLM-D projects, 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.
As a Senior Engineering Manager of the Machine Learning Engineering team focused on vLLM inference, you will be at the forefront of innovation, collaborating with our team to tackle the most pressing challenges in model performance and efficiency. Your technical and people leadership with machine learning and high performance computing will directly impact the development of our cutting-edge software platform, helping to shape the future of AI deployment and utilization. You would be joining the core team behind 2025's most popular open source project on GitHub . If you are someone who wants to contribute to solving challenging technical problems at the forefront of deep learning in the open source way, this is the role for you.
Join us in shaping the future of AI Inference!
What you will do
Setting the overarching vision, objectives, and strategies for a group of engineering teams and engineering managers.
Lead and inspire a distributed team of individual contributors and managers, fostering a collaborative and innovative work environment.
Engage with the AI and machine learning open source communities such as vLLM , llm-d , and other open source communities.
Work with product management and engineering teams to develop technology roadmaps and schedules, and communicate these schedules externally.
Work with cross-functional engineering managers and teams on documentation, product management, and quality assurance to coordinate tasks necessary for releasing enterprise-quality MLOps software.
Working closely with the technical leads and scrum leads to direct the team in agile development.
Meet and present technical presentations to customers and partners as necessary.
Mentor and nurture team members in their career development, and professional growth.
Recruit and build a world class engineering team.
What you will bring
10 years of significant hands-on software development and system design experience
5 years of experience in managing software engineering teams
Proven experience in leading machine learning engineering teams, with a track record of successful project delivery and development of software engineers and engineering managers
Experience in machine learning frameworks and tools, such as PyTorch, and HuggingFace.
Extremely proficient in running and analyzing LLM performance and accuracy benchmarks across a variety of accelerators.
Excellent programming skills in languages like Python, and C/CUDA .
Experience with developing and scaling applications with Kubernetes.
Excellent written and verbal communication skills.
Ability to lead and work with diverse and distributed teams from multiple countries and cultures.
#LI-MD2
#AI-HIRING
The salary range for this position is $210,730.00 - $358,070.00. 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 commu ... (truncated, view full listing at source)
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