Senior Software Engineer - Machine Learning
Pubblicato il 10-08-2026 - Altro in Roma
Do you want to design and build the tools that enable creation of the next generation of Foundation Models and Large Language Models (LLMs)? The Red Hat OpenShift AI (RHOAI) engineering team is seeking a Principal Software Engineer with Kubernetes and MLOps experience to join our rapidly growing Distributed Model Training platform team. Our team creates the tools necessary for enterprise data science teams to leverage distributed compute infrastructure across the hybrid cloud when training today’s most complex ML models.
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In this role, you'll be contributing as an expert on ML model training and the tools necessary to support it at enterprise scale. Your contributions will enable bleeding edge platform capabilities around distributed computation and model training, model hyperparameter tuning, kubernetes-native job scheduling, and kubernetes-native resource optimization. This is an extraordinary opportunity to contribute to the development of the RHOAI family of products, participate in open source communities such as Kubeflow, Kubernetes, Ray, and Kueue, and be at the forefront of the exciting evolution of AI.
The future of the AI industry is open with extensive opportunities, and RHOAI is a strategic investment area for Red Hat. You'll join an ecosystem that fosters continuous learning, career growth, and professional development. This hands‑on experience is a great way for you to get first‑hand exposure to the AI landscape.
Are you ready to start developing new solutions that combine open source, hybrid cloud, and AI? Join the Red Hat OpenShift AI team!
What you will do
Lead Red Hat’s participation in machine learning related upstream communities to ensure the technologies work on OpenShift and can be integrated with RHOAI
Architect and lead implementation of scalable open source solutions for Data Scientists to leverage distributed computing capabilities to train their Machine Learning models, running on OpenShift
Act as a MLOps SME within Red Hat by supporting customer‑facing discussions, presenting at technical conferences, and evangelizing OpenShift AI within the internal community of practice
Architect and design new features for open source communities such as Kueue, KubeRay, PyTorch, KubeFlow, and CodeFlare
Provide technical vision and leadership on critical and high impact projects
Mentor, influence, and coach a distributed team of engineers
Present at OpenShift/Kubernetes, and AI/ML related technology conferences and internally within the AI/ML communities of practice
What you will bring
An existing contributor in one or more MLOps open source projects such as Ray/KubeRay, KubeFlow, Pytorch, Katib
Experience training and tuning ML models using tools like Ray, Kubeflow training operator, Katib, MLFlow, or similar
Advanced level of experience with Kubernetes
Advanced level knowledge and experience in development in Go or Python
Excellent system understanding and troubleshooting capabilities
Solid innovation skills and a passion for technology
Technical leadership acumen in a global xysqume team environment & mentorship experience
Passion for writing and maintaining reliable code
Excellent written and verbal communication skills; good English language skills
The following will be considered a plus
Bachelor's degree in statistics, mathematics, computer science, operations research, or a related quantitative field, or equivalent expertise; Master’s or PhD
Experience in engineering, consulting or another field related to distributed model training or data processing in a customer environment or supporting a data science team
Highly experienced in OpenShift
Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.
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