
HP Hiring College Intern 2025 | Market Standard
HP
Internship
💸 Market Standard
💼 College Intern
🎓 Bachelor/Master/PhD
📅 Internship
🚀 Bangalore
🕓 Posted on 15 March
2025
Job Description For HP Internship 2025 :
Job Details
HP is looking for an individual to join the AI Lab team as a summer intern. This team is responsible for exploring and pushing the boundaries of state-of-the-art applied Gen AI research with a focus on edge applications. The candidate will be involved in the research and development of generative AI models and will work with other team members to develop novel ideas and proof-of-concept prototypes, potentially leading to publications. The role will involve research and development in the area of model optimization for edge use cases.
Responsibilities
- Proposes innovations that improve on the state of the art.
- Develops/fine-tunes Generative AI models for target applications.
- Conducts analysis and benchmarking to show improved model performance.
- Implements alternative approaches and baselines from the latest research.
Education & Experience Recommended
- Enrolled in Bachelor/Master/PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or any other related discipline.
- Typically has finished formal courses in any or all of the following areas: data analytics, statistical modeling, machine learning, deep learning.
Knowledge and Skills
Required:
- Algorithms
- Basic Deep Learning
- Machine Learning (Classification, Regression, Bagging, Boosting)
- Natural Language Processing
- Python Programming & PyTorch Framework
- Hugging Face Library (practical knowledge of fine-tuning using LoRA/QLoRA)
- Experience with Git workflow (staging, commit, push, pull request, branching, merging)
Good to Have:
- Basic Transformers implementation from scratch using PyTorch
- Architectural knowledge of LLaMA, MoE models
- Knowledge of how to interact with small gaming environments like Atari for Deep RL algorithms
- Skill in systems engineering, high-performance computing, with a strong emphasis on efficient implementations
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