Senior Machine Learning Engineer - OpenShift AI Observability

Job Summary:
Are you ready to join a game-changing open-source AI platform that harnesses the power of hybrid cloud to drive innovation?

The Red Hat OpenShift AI (RHOAI) 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. You’ll 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.

At Red Hat, our commitment to open source innovation extends beyond our products - it’s embedded in how we work and grow. Red Hatters 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

What you will bring

Experience in machine learning engineering, with a focus on production-grade systems

Proficiency in Python with a focus on AI/ML infrastructure or tooling

Experience working with Kubernetes, OpenShift, or other cloud-native platforms

Familiarity with ML observability tools (e.g. Prometheus, OpenTelemetry, and Grafana)

Hands-on experience with source control tools such as Git

Passion for open-source technology and collaborative development

Strong troubleshooting skills and system-level thinking

Ability to work autonomously and thrive in a fast-paced environment

Excellent written and verbal communication skills

The following will be considered a plus:

Master’s degree or higher in computer science, machine learning, or related discipline

Contributions to open-source projects, especially in the MLOps or ML observability domain

Experience with public cloud services (AWS, GCP, Azure)

Background in developing or deploying MLOps platforms or AI monitoring tools

Demonstrate proficiency in utilizing LLMs (e.g., Google Gemini), as relevant, for tasks such as brainstorming solutions, deep research, summarizing technical documentation, drafting communications, summarizing complex technical information, and enhancing problem-solving efficiency across the development lifecycle.

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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 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. 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.

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)
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