Senior Software Engineer - Machine Learning
Pubblicato il 21-10-2026 - Red Hat in Italia
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 Open Shift 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.
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 Open Shift AI team!
What you will do
Lead Red Hat's participation in machine learning related upstream communities to ensure the technologies work on Open Shift 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 Open Shift Act as a MLOps SME within Red Hat by supporting customer?facing discussions, presenting at technical conferences, and evangelizing Open Shift AI within the internal community of practice Architect and design new features for open source communities such as Kueue, Kube Ray, Py Torch, Kube Flow, and Code Flare Provide technical vision and leadership on critical and high impact projects Mentor, influence, and coach a distributed team of engineers Present at Open Shift/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/Kube Ray, Kube Flow, 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 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 Ph D 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 Open Shift 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.