Red hat Senior MLOps Engineer - OpenShift AI 

Ireland 

489184709

Job Responsibilities

• Lead the architecture and implementation of MLOps/LLMOps systems within OpenShift AI, establishing best practices for scalability, reliability, and maintainability while actively contributing to relevant open source communities

• Design and develop robust, production-grade features focused on AI trustworthiness, including model monitoring, bias detection, and explainability frameworks that integrate seamlessly with OpenShift AI

• Drive technical decision-making around system architecture, technology selection, and implementation strategies for key MLOps components, with a focus on open source technologies like KServe and TrustyAI

• Define and implement technical standards for model deployment, monitoring, and validation pipelines, while mentoring team members on MLOps best practices and engineering excellence

• Collaborate with product management to translate customer requirements into technical specifications, architect solutions that address scalability and performance challenges, and provide technical leadership in customer-facing discussions

• Lead code reviews, architectural reviews, and technical documentation efforts to ensure high code quality and maintainable systems across distributed engineering teams

• Identify and resolve complex technical challenges in production environments, particularly around model serving, scaling, and reliability in enterprise Kubernetes deployments

• Partner with cross-functional teams to establish technical roadmaps, evaluate build-vs-buy decisions, and ensure alignment between engineering capabilities and product vision

• Provide technical mentorship to team members, including code review feedback, architecture guidance, and career development support while fostering a culture of engineering excellence

Required Qualifications

• 5+ years of software engineering experience, with at least 4 years focusing on ML/AI systems in production environments

• Strong expertise in Python, with demonstrated experience building and deploying production ML systems

• Deep understanding of Kubernetes and container orchestration, particularly in ML workload contexts

• Extensive experience with MLOps tools and frameworks (e.g., KServe, Kubeflow, MLflow, or similar)

• Track record of technical leadership in open source projects, including significant contributions and community engagement

• Proven experience architecting and implementing large-scale distributed systems

• Strong background in software engineering best practices, including CI/CD, testing, and monitoring

• Experience mentoring engineers and driving technical decisions in a team environment

Preferred Qualifications

• Experience with Red Hat OpenShift or similar enterprise Kubernetes platforms

• Contributions to ML/AI open source projects, particularly in the MLOps space

• Background in implementing ML model monitoring, explainability, or bias detection systems

• Experience with LLM operations and deployment at scale

• Public speaking experience at technical conferences

• Advanced degree in Computer Science, Machine Learning, or related field

• Experience working with distributed engineering teams across multiple time zones

• Familiarity with AI governance and responsible AI practices