Red Hat's Global Engineering team is looking for an experienced Senior Machine Learning Engineer to join the Agentic and AI Engineering Tools team to contribute to Red Hat’s rapidly growing AI/ML family of products and be responsible for the investigation, evaluation, integration, and development of open source AI/ML systems and functionality to improve the overall development and operations of both Red Hat’s downstream AI products and upstream open source AI projects.
Requirements
- Experience writing unit, functional, and end-to-end tests for predictive or generative AI applications.
- Experience preparing structured datasets for training and analysis.
- Experience with feature engineering to enhance the utility of ML models.
- Experience with model performance evaluation using predefined metrics to assess model accuracy and identify improvements.
- Experience deploying machine learning models into test environments.
- Experience building agentic systems with MCP, ACP, or A2A.
- Experience working with Kubernetes/OpenShift and containers, troubleshooting issues with them, and working with YAML, Kubernetes controllers, and operators.
Responsibilities
- Build developer-facing capabilities to enable agentic reasoning using large language models.
- Establish best-practices for using those capabilities effectively.
- Enable developers to evaluate how effective and reliable the agentic reasoning system they create are.
- Provide scalable, secure, and robust infrastructure for tools used in agentic reasoning.
- Work with software engineers , data scientists, and product managers to meet project requirements.
- Provide technical guidance and training to junior engineers
- Train ML models using established frameworks and architectures.
Other
- 5+ years of experience as a Machine Learning Engineer, Software Engineer, Data Scientist, or similar role.
- Bachelor's degree in Computer Science or related discipline.
- Machine learning, AI, or deep learning-related course work or experience or independent project work with evidence of completion.
- Experience in understanding and implementing concepts outlined in research papers.
- Participating in an agile development team.
