Red Hat Off Campus Drive 2025 hiring Trainee

Red Hat hiring Trainee

Company: Red Hat
Qualifications: Graduate degree in AI, Data Science, CS
Experience Needed: Freshers
Location: Pune

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

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