The Red Hat Emerging Technologies team within the Office of the CTOis looking for a data scientist to join us as a full-time employee, preferably in Ireland (strong preference for one of our office locations: Waterford, Cork, or Dublin. You will join our AI engineering team, a team whose project work consists primarily of investigation, evaluation, and development of open source AI/ML/DS systems and functionality to improve the overall development and operations of Red Hat’s product portfolio. You will also collaborate with other engineering teams within Red Hat to develop new data science and analytics components and extend the machine learning capabilities of existing systems. The ideal candidate is energized by working concurrently on a wide variety of projects, independently as well as within a team environment.

What you will do

• Participate in a variety of software and system integration projects in different programming languages with a focus on addressing machine learning and data science challenges.
• Work concurrently on multiple projects (usually in the range of 3 to 12 months), independently and within a team environment.
• Develop innovative capabilities for open source platforms used for building, training, testing, and serving models for AI-enabled applications.
• Participate in upstream data science and machine learning project communities.
• Evaluate new machine learning and data science technologies.
• Communicate about machine learning and data science technologies and ongoing machine learning and data science projects with a variety of technical and non-technical stakeholders.
• Collaborate with Red Hat product engineering teams and external partners, such as IBM Research, to align on strategic vision, transition project ownership, and coordinate key implementation details.
• Share our experiments and learnings from an experienced position in the Data Science community through blogs, presentations, new ideas and existing work at various technical outlets and conferences.
• Promote upstream acceptance and community building.

What you will bring

• Advanced programming skills in Python.
• Experience with Cloud Native Technologies and Platforms (e.g. Kubernetes).
• Demonstrates knowledge of unit testing frameworks and methodologies.
• Data science-related course work or independent project work with evidence of completion.
• Strong self-motivation and organizational skills.
• Demonstrates ability to context switch between multiple concurrent projects.
• Collaborative attitude and willingness to share ideas openly.
• Excellent English written and verbal communication skills.

The following are considered a plus

• Experience with Linux (e.g. RHEL, Ubuntu, etc…), Rest APIs, and containers.
• Passion for developing open source software.

LI-KS1

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 have the flexibility to choose the work environment that suits their needs from in-office to fully remote to office-flex. 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. Opportunities are open. Join us.
Diversity, Equity & 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 diverse 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 of diversity 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.
Red Hat supports individuals with disabilities and provides reasonable accommodations to job applicants. If you need assistance completing our online job application, email
application-assistance@redhat.com
. General inquiries, such as those regarding the status of a job application, will not receive a reply

• Participate in a variety of software and system integration projects in different programming languages with a focus on addressing machine learning and data science challenges.
• Work concurrently on multiple projects (usually in the range of 3 to 12 months), independently and within a team environment.
• Develop innovative capabilities for open source platforms used for building, training, testing, and serving models for AI-enabled applications.
• Participate in upstream data science and machine learning project communities.
• Evaluate new machine learning and data science technologies.
• Communicate about machine learning and data science technologies and ongoing machine learning and data science projects with a variety of technical and non-technical stakeholders.
• Collaborate with Red Hat product engineering teams and external partners, such as IBM Research, to align on strategic vision, transition project ownership, and coordinate key implementation details.
• Share our experiments and learnings from an experienced position in the Data Science community through blogs, presentations, new ideas and existing work at various technical outlets and conferences.
• Promote upstream acceptance and community building