About the job
The Red Hat Global Support Services is looking for a motivated and passionate Trainee who is eager to learn about AI/ML, Data Science and deploy solutions as we modernize platforms and tooling.
At the end of 6 months, as an Associate Data Scientist you’d be working on issues to implement AI / ML solutions and any troubleshooting thereof and RHEL AI which is a Generative AI focussed platform. You will also be working closely with the product management, other engineering groups within Red Hat, and with Red Hat partners. This is a perfect opportunity for fresh graduates eager to learn and grow in the field of AI.
What will you do?
Complete AI / ML, Data Science Trainings
Work on efficiency projects pertaining to AI
Work on prototypes for innovation
Learn Red Hat technologies such as RHEL AI that will help to contribute to real-time use cases and problems
What will you bring?
Graduate degree in Computer Science, AI, Data Science
Foundational NLP Concepts
Knowledge of data visualization, data preprocessing and data analysis with standard NLP libraries like Spacy, NLTK, etc
Strong Foundation in Python programming
Familiarity with AI/ ML frameworks such as TensorFlow, PyTorch, Numpy
Knowledge of AI hardware accelerators such as GPUs
Understanding of cloud platforms such as AWS, GCP, Azure for AI model deployment
Ethics - Understanding of AI Ethics and responsible AI development
Proficient written and verbal communication skills in English
Ability and willingness to adapt to new technologies and tools as the AI field evolves
Ability to work with conflicting priorities, take initiative, and maintain a customer-centric focus
Excellent problem-solving and debugging skills to resolve technical issues
Ability to work independently and as part of a globally distributed team of engineers
The following is considered a plus
Any contribution to AI/ ML project at University / personal level
Familiarity with DevOps practices for AI/ML model deployment, such as CI/CD pipelines and containerization (e.g., Docker, Kubernetes)
Familiarity with open-source development and contribution to open-source AI/ML projects (GitHub, GitLab, etc.)
Understanding of foundational concepts in generative AI and LLMs, including transformers, attention mechanisms, and fine-tuning large models
Familiarity with building and deploying machine learning models, such as regression, classification, and forecasting, along with hands-on experience in evaluating their performance
About Red Hat
Red Hat is the world’s leading provider of enterpriseopen 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.
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.