Principal Machine Learning Engineer – Model Training and CustomizationJob Summary Come be a part of Red Hats charge to democratize AI with open source! Red Hats Global Engineering Team is looking for a Principal Machine Learning Engineer to join our newly formed AI Engineering organization. This role will be located within the AI Innovation team, which conducts customer- and science-driven research to drive innovation for Red Hats customers. The team focuses on a pattern of research → open-source software → product as the way we operate our engineering work. This role will be focused on architecting and building the core logic and enhancements for our model fine-tuning and post-training libraries. In this role, you will work directly with research scientists and open source AI communities to design, build, and improve implementations of novel training methods, ranging from SFT, continual learning, and offline preference tuning to online reinforcement learning methods like GRPO and RLHF. You will develop working relationships across multiple teams, driving contributions to both upstream open source projects and our internal Training Hub, while providing technical leadership on architecture decisions and implementation strategies. The ideal candidate will be a highly collaborative individual with a passion for working on complex ML projects in an open organization where contributions are valued and expected from all levels. As this is a fast-moving area of opportunity for Red Hat, the ability to communicate productively and effectively with team members and stakeholders is critical. Success in this role would be delivering robust, scalable training libraries that bridge cutting-edge research with production needs while establishing technical standards and best practices. This position reports directly to the Manager of AI Innovation. This position may require occasional travel to partner collaboratively in our Boston, MA office multiple times per quarter. Successful applicants must reside in a state where Red Hat is registered to do business.What you will do Architect and develop core libraries for various model post-training methods and innovations. Lead technical design decisions for training infrastructure and algorithm implementations. Work directly on upstream, open source projects and engage with community needs and contributions. Drive core post-training algorithm research and engineering, introducing new methods both to community efforts and our own Training Hub. Understand and adapt novel architectures and techniques to work with various post-training algorithms, across distributed training frameworks. Optimize, enhance, and improve robustness and usability of both existing and in-flight projects, working closely with researchers to validate prototype logic. Maintain and expand library feature pool, and address core algorithm bugs and blockers. Collaborate with software engineers on interface and testing designs, establishing architectural patterns and standards. Lead code reviews and establish best practices within the engineering team. Document system designs, processes, and model performance for transparency and future reference. Report on project status, challenges, and results to stakeholders. Serve as a technical lead for training and customization components, providing guidance to build knowledge and capabilities within the team.  What you will bring Bachelors degree in computer science or equivalent. Advanced experience in Python development. Deep background in AI/ML projects (neural networks, deep learning, language models, reinforcement learning). Proven experience in research engineering, machine learning engineering, or applied ML roles. Expert-level experience with common model architecture development and adapter frameworks (e.g. PyTorch, Transformers, PEFT, etc.). Strong experience with distributed training frameworks (e.g. FSDP, DeepSpeed) and inference runtimes (e.g. vLLM). Demonstrated experience in open-source projects and collaborative development workflows. Strong background in software development or engineering, building robust and consumable libraries and implementations. Experience with unit testing, integration testing, and performance testing. Experience designing and implementing complex ML systems at scale. Strong self-motivation and organizational skills. Ability to handle multiple concurrent projects effectively. Strong technical leadership and collaboration skills. Excellent written and verbal communication skills. Positive attitude and willingness to share ideas openly. Considered a plus Masters or PhD in Machine Learning (ML) / Natural Language Processing (NLP). Experience with MLOps and deployment systems (e.g., Kubeflow, MLflow, Kubernetes, CI/CD pipelines). Experience writing functional, end-to-end or coverage tests in Python. Experience with GitHub Actions, GitHub automation, or CI/CD practices. Experience reading/writing, publishing, and/or implementing research papers. Experience with Red Hat products. Deep experience with large language models and their training methodologies. Contributions to major open-source ML frameworks or libraries. Experience leading technical initiatives in ML infrastructure. #LI-JC2 #AI-HiringThe salary range for this position is $189,600.00 - $312,730.00. Actual offer will be based on your qualifications.Pay TransparencyRed 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<a href="https://www.redhat.com/" target="_blank">Red Hat</a> is the world’s leading provider of enterprise<a href="https://www.redhat.com/en/about/open-source" target="_blank"> open source</a> 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. Were 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. 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