Engineering Manager – Machine Learning Full-time

Job Summary

Do you want to be part of a team that is focused on scaling the deployment, tuning, and monitoring of Foundation Models and large language models? Do you want to play a pivotal role in shaping the roadmap and strategy for OpenShift AI serving with the large language models? We are seeking an experienced and dynamic Engineering Manager to lead our fast growing and globally distributed engineering team.

The ideal candidate will combine strong technical expertise in model serving, MLOps, and Responsible AI with stellar leadership and managerial skills.. As an engineering manager, you will be responsible for guiding the development and deployment of model serving and model metrics & monitoring by driving innovation, and ensuring the successful execution of projects. This role requires a strategic thinker who can align open source initiatives with business goals and foster a collaborative and high-performance team culture.

We will considers candidates located in any European location where Red Hat is registered to hire.

Primary job responsibilities

• Lead and inspire a distributed team of individual contributors, fostering a collaborative and innovative work environment.
• Engage with the AI and machine learning open source communities such as KServe, TrustyAI, Kubeflow, HuggingFace, vLLM, and several 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.
• Mentor and nurture team members in their career development, and professional growth.
• Recruit and build a world class engineering team.
• Work closely with engineers and researchers on Red Hat OpenShift, Red Hat Enterprise Linux, and Red Hat Middleware teams to provide end-to-end AI/ML capabilities.

What You Will Bring

• 5+ years of significant hands-on software development and system design experience.
• 2+ years of 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.
• Experience in machine learning frameworks and tools, such as PyTorch, and HuggingFace.
• Excellent programming skills in languages like Python, or Go.
• Experience with developing and scaling applications with Kubernetes.
• Solid understanding of core machine learning concepts.
• Excellent written and verbal communication skills.
• Ability to lead and work with diverse and distributed teams from multiple countries and cultures.

#LI-AM4

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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 have the flexibility to choose the work environment that suits their needs from in-office to fully remote to office-flex. 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. Opportunities are open. Join us.

Diversity, Equity & 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 diverse 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 of diversity that compose our global village.

Equal Opportunity Policy (EEO)
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