Job Summary:
The Portfolio and Delivery Department within Red Hat's Global Engineering organization is responsible for streamlining product development lifecycle, improving delivery efficiency, ensuring product quality and much more. We are a data-driven organization, and we are expanding our capabilities in Generative AI to further optimize our processes and create innovative solutions.
We are seeking an enthusiastic and skilled Data Scientist to join our team and contribute to the implementation of Generative AI solutions. In this role, you will work on exciting projects that leverage cutting-edge AI technologies to improve our product delivery processes, enhance efficiency and drive innovation. You will collaborate with a team of experienced data scientists, engineers, and product managers to develop and deploy GenAI-powered applications.
What you will do:
Collaborate with cross-functional teams to identify opportunities for applying Generative AI to solve problems in product delivery.
Work with cutting edge generative developer tools and application in a fast moving adaptive environment.
Assist in the design, development, and implementation of GenAI solutions, utilizing agentic methodologies, for various use cases (e.g., code generation, documentation automation, process optimization etc.).
Work with large datasets, performing data cleaning, preprocessing, and feature engineering to prepare data for GenAI models.
Evaluate and fine-tune GenAI models to ensure optimal performance, accuracy, and efficiency.
Develop and maintain pipelines for deploying and monitoring GenAI solutions in a production environment using Red-Hat’s platform stack.
Stay up-to-date with the latest advancements in Generative AI and related technologies.
Document your work, including code, models, and results, and communicate findings to both technical and non-technical audiences.
Contribute to the development of best practices for GenAI implementation within the organization.
Work in an open and collaborative environment, contributing to Red Hat's open-source culture.
What you will bring:
Bachelor's degree in Computer Science, Mathematics, Statistics, or a related quantitative field. A Master's degree is a plus.
At least 2 years of experience as a Data-Scientist.
Strong understanding of machine learning fundamentals and experience with common machine learning algorithms.
Experience with Python and relevant libraries such as TensorFlow, PyTorch, or Hugging Face Transformers.
Familiarity with Large Language Models (LLMs) and their applications.
Experience with data manipulation and analysis using tools like Pandas and SQL.
Ability to work independently and as part of a team in a fast-paced environment.
Strong problem-solving skills and a passion for working with data.
Excellent communication and interpersonal skills.
A passion for open-source software and technology.
The following is considered a plus:
Experience with deploying machine learning models in a production environment.
Knowledge of cloud computing platforms (e.g. AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
Experience with MLOps practices and tools.
Experience with generative developer tools (e.g. Cursor, Claude-Code, Copilot)
Familiarity with Red Hat technologies.
Contributions to open-source projects.
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About Red Hat
Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact.
Inclusion at Red Hat
Red Hat’s culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from different backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions that compose our global village.
Equal Opportunity Policy (EEO)
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.
Red Hat does not seek or accept unsolicited resumes or CVs from recruitment agencies. We are not responsible for, and will not pay, any fees, commissions, or any other payment related to unsolicited resumes or CVs except as required in a written contract between Red Hat and the recruitment agency or party requesting payment of a fee.
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