Generative AI/ML Internship
Digital Blaize
Recruitment Process
Screening
Interview
You'll have a live interview with our hiring team, analyzing your responses in real-time to provide evaluators with deeper insights. This helps us have a more objective conversation about your experience and fit. Please Complete the Google form https://docs.google.com/forms/d/e/1FAIpQLSeIghGjzGZCv3aqQYgUI46gcdwofdLeXj-tYFvOYXVYf2JTvA/viewform?usp=header
Interview
Interview round
Details
Responsibilities:
- Fine-tune open-source LLMs (LLaMA 3, Mistral, GPT-2, Quen2 ) using LoRA/QLoRA techniques for domain-specific use cases
- Collect, clean, preprocess, and structure training datasets for model development
- Design and run prompt engineering and evaluation workflows to optimize model outputs
- Build and test RAG (Retrieval-Augmented Generation) pipelines using vector databases like ChromaDB or FAISS
- Experiment with RLHF (Reinforcement Learning from Human Feedback) and model optimization strategies
- Develop evaluation benchmarks measuring reasoning, accuracy, and generation quality
- Assist in deploying fine-tuned models via APIs (FastAPI/Flask) for integration with web products
- Collaborate with the engineering team, document experiments, and present findings regularly
Requirements:
Must-Have
- Pursuing or recently completed a degree in Computer Science, AI/ML, Data Science, or a related field
- Strong Python programming skills (NumPy, pandas, scikit-learn)
- Hands-on familiarity with Hugging Face Transformers, PyTorch, or TensorFlow
- Understanding of ML fundamentals: training loops, loss functions, evaluation metrics
- Basic knowledge of LLMs, embeddings, and fine-tuning concepts
Good to Have
- Experience working with LLaMA, Mistral, Falcon, or similar open-source models
- Familiarity with LoRA, QLoRA, PEFT parameter-efficient fine-tuning methods
- Prior exposure to LangChain, LlamaIndex, or vector databases
- Basic understanding of REST APIs or Flask/FastAPI backends
- Access to a GPU environment (Colab Pro, Kaggle, or local GPU) is a plus
What You'll Gain:
- Real-world experience building production-grade LLM pipelines
- Hands-on training under an experienced AI team at Digital Blaize
- Certificate of Completion + Letter of Recommendation
- Potential Pre-Placement Offer (PPO) for high performers
- Exposure to the full AI lifecycle — from data collection to model deployment
Important dates & deadlines?
-
4 Jul'26, 12:00 AM IST Registration Deadline
Additional Information
Stipend
Work Detail
Working Days: 5 Days
Schedule: Flexible Work Hours, Monday to Friday,
Job Type/Timing
Job Type: Work From Home
Job Timing: Full Time
Perks
Job Offer
Certificate of Completion
Letter of Recommendation
Flexible Hours
Hybrid Working
Counselling Support
Pre-Placement Offer