Senior Machine Learning Engineer, RHEL Lightspeed

At Red Hat, we connect an innovative community of customers, partners, and contributors to deliver an open source stack of trusted, high-performing solutions. We offer cloud, Linux, middleware, virtualization, and AI technologies, together with award-winning global customer support, consulting, and implementation services. Red Hat is a rapidly-growing company supporting more than 90% of Fortune 500 companies.

Job Summary

Where better to define the intersection of open source and AI than at Red Hat, the open source leader? Here's a rare opportunity: apply your machine learning skills to help enable the next generation of Red Hat Enterprise Linux (RHEL), an industry-leading operating system, using AI.

Red Hat's RHEL Lightspeed team is looking for a Machine Learning Engineer to join us in evolving the Linux operating system to an AI-enabled, next generation OS. We want to enable Linux users to more easily build what they need and to operate more efficiently with RHEL.

In this role, you will develop working relationships across multiple teams, planning and prioritizing sprint work across a small team, along with direct contribution to open source development projects.  The ideal candidate will be a highly collaborative individual with a passion for working on complex projects in an open organization where contributions are valued and expected from all levels. Clear and empathetic communication is critical, and you will be looked to as an action-oriented key subject matter expert.

What you will do

• Run experiments, tests, and large-scale distributed jobs in support of AI product features.

• Lead a variety of coding projects in different programming languages with a focus on addressing machine learning and data science challenges.

• Participate in and lead in upstream open source projects as an AI/ML expert.

• Evaluate new machine learning and data science technologies.

• Evangelize, communicate, and promote machine learning and data science technologies and ongoing machine learning projects with a variety of technical and non-technical stakeholders.

• Transition software components from research into product.

• 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.

What you will bring

• Bachelor's degree in computer science or equivalent.

• Machine learning, AI, or deep learning-related course work or independent project work with evidence of completion.

• Experience in understanding and implementing concepts outlined through research papers. Experience with writing and publication of research papers is a plus.

• Advanced programming skills in Python and SQL.

• Demonstrable knowledge of machine learning relevant mathematics and statistics.

• Strong self-motivation and organizational skills.

• Giftedness and passion for explaining machine learning concepts in an accessible way to others in order to enable shared outcomes.

• Demonstrable ability to context switch between multiple concurrent projects.

• Excellent written and verbal communication skills.

• Positive attitude and willingness to share ideas openly.

Other skills

• Masters or PhD in Machine Learning (ML) / Natural Language Processing (NLP).

• Experience with Red Hat Enterprise Linux (RHEL), Rest APIs, Kubernetes, and containers.

• 2+ years of direct experience developing and using Data Visualization tools and Jupyter notebooks.

• Demonstrates knowledge of unit testing frameworks and methodologies.

• Familiarity with participating in an agile development team.

Growth Mindset Statement: 

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 hig