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The OpenShift AI team is looking for a Machine Learning Engineer with experience in building, scaling, and monitoring AI/ML systems to join our rapidly growing engineering team. Our focus is to create a platform, partner ecosystem, and community by which enterprise customers can solve problems to accelerate business success using AI. This is a very exciting opportunity to shape the deployment and reliability of GenAI workloads, contribute to the development of the RHOAI product, participate in open source communities, and be at the forefront of the exciting evolution of AI. Youll join an ecosystem that fosters continuous learning, career growth, and professional development.
As a core ML engineer for one of our OpenShift AI teams, you will have the opportunity to design and build systems that monitor, validate, and improve AI model performance in production. You will work as part of an evolving development team to rapidly design, secure, build, test, and release new capabilities. The role is primarily an individual contributor who collaborates closely with other ML engineers, software developers, and cross-functional teams. You should have a passion for observability, MLOps, and building robust systems for real-world AI.
Our commitment to open source innovation extends beyond our products - its embedded in how we work and grow. we embrace change especially in our fast-moving technological landscape and have a strong growth mindset. That's why we encourage our teams to proactively, thoughtfully, and ethically use AI to simplify their workflows, cut complexity, and boost efficiency. This empowers our associates to focus on higher-impact work, creating smart, more innovative solutions that solve our customers' most pressing challenges.
What you will do:
Design and build observability and assistance tools to help customers optimize large-scale AI initiatives running on Kubernetes
Innovate in the MLOps and AI observability and deployment optimization domains by contributing to upstream communities
Collaborate with product, engineering, and research teams to improve model trust and performance
Write unit and integration tests and work with quality engineers to ensure product quality
Use CI/CD best practices to deliver solutions into RHOAI as part of our productization efforts
Proactively utilize AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code) for code generation, auto-completion, and intelligent suggestions to accelerate development cycles and enhance code quality.
Contribute to a culture of continuous improvement by sharing technical knowledge and insights
Communicate effectively with stakeholders and team members to ensure visibility of ML performance
Represent RHOAI in external engagements including open source communities and customer meetings
Mentor and guide junior engineers and contribute to team growth
Explore and experiment with emerging AI technologies relevant to software development, proactively identifying opportunities to incorporate new AI.

The Ecosystems Engineering group is seeking a Senior Principal Software Engineer to join our rapidly growing team. This is a game-changing opportunity to join an open-source AI platform that harnesses the power of hybrid cloud to drive innovation. In this role, you will work with a diverse team of highly talented engineers on designing, implementing, and productizing new AI solutions, with a focus on deep integration of the AI stack, hardware accelerators, and leading OEMs and Cloud Computing Service Providers (CCSPs).
You'll play a critical role in shaping the next generation of hybrid cloud platforms by directly contributing to our innovative AI and Edge products. This is your chance to be at the forefront of AI's exciting evolution, joining an ecosystem that champions continuous learning, career growth, and professional development. You'll also collaborate closely with product management, other engineering teams, and key partners and lighthouse customers.
What You Will Do:
Architect and lead the implementation of new features and solutions for our AI and Edge products.
Explore deep code integration into various products, ensuring optimal integration between our portfolio, hardware accelerators and partners.
Provide technical vision and leadership on critical and high-impact projects, ensuring non-functional requirements including security, resiliency, and maintainability are met.
Integrate software that leverages hardware accelerators (e.g., DPUs, GPUs, AIUs) and perform performance analysis and optimization of AI workloads with accelerators.
Work with major AI and hardware partners such as NVIDIA, AMD, Dell, and others on building joint integrations and products.
Collaborate closely with UX, UI, QE, and cross-functional teams to deliver a great experience to our partners and customers.
Coordinate with team leads, architects, and other engineers on the design and architecture of our offerings.
Become responsible for the quality of our offerings, participate in peer code reviews and continuous integration (CI), and respond to security threats.
Mentor, influence, and coach a distributed team of engineers, contributing to a culture of continuous improvement by sharing recommendations and technical knowledge.

The Engineering team is looking for a Senior Integration Engineer to join our Edge Infrastructure Group. In this role, you will be part of a team responsible for designing and implementing the container platform for enterprises and telecommunication companies and contributing to industry-leading technologies in the Kubernetes ecosystem. As a part of a geographically distributed team, you will collaborate with multiple engineering teams and open source communities around the globe. To be successful in this role, you'll need to have motivation, curiosity, passion for problem-solving, and experience with Linux technologies and open source.
What You Will Do
Play an active role applying Kubernetes and OpenShift to customer use cases
Develop and integrate changes in multiple projects using open source methodologies to provide end-to-end solutions
Troubleshoot, analyze bug root causes, and provide resolutions
Review design, enhancement proposal, and patches from other team members and other collaborators
Work with various engineering team to ensure products are developed and tested correctly
Publicize the team's work through blogs, web postings, or conference talks
Stay up-to-date on the latest advancements in AI frameworks, and leverage those in your day to day work.