Python
Machine Learning (ML)Role Overview
We're looking for a highly motivated AI Intern to join our dynamic team. This isn't your average internship; you'll be diving headfirst into the exciting world of Natural Language Processing (NLP) and Large Language Models (LLMs). You will work on real-world projects, contributing directly to our core products by researching, developing, and fine-tuning state-of-the-art language models. If you're passionate about making machines understand and generate human language, this is the perfect role for you!
Skills Needed:
- Python
- ML
- NLP
- LLM Fine-Tuning
- Fast API
What You'll Do (Key Responsibilities)
Develop & Implement LLM Models: Assist in building and deploying LLM solutions for tasks like sentiment analysis, text summarization, named entity recognition (NER), and question-answering.
Fine-Tune LLMs: Work hands-on with pre-trained Large Language Models (like Llama, GPT, BERT) and fine-tune them on our custom datasets to enhance performance for specific tasks.
Data Pipeline Management: Be responsible for data preprocessing, cleaning, and augmentation to create high-quality datasets for training and evaluation.
Experiment & Evaluate: Research and experiment with different model architectures and fine-tuning strategies (e.g., LoRA, QLoRA) to optimize for accuracy, speed, and cost.
Collaborate & Document: Work closely with our senior ML engineers and data scientists, actively participating in code reviews and clearly documenting your findings and methodologies.
Must-Have Skills (Qualifications)
Strong Python Proficiency: You live and breathe Python and are comfortable with its data science ecosystem (Pandas, NumPy, Scikit-learn).
Solid ML & NLP Fundamentals: A strong theoretical understanding of machine learning algorithms, deep learning concepts, and core NLP techniques (e.g., tokenization, embeddings, attention mechanisms).
Deep Learning Frameworks: Hands-on experience with either PyTorch or TensorFlow.
Familiarity with LLMs: You understand the basics of transformer architecture and have some exposure to working with or fine-tuning Large Language Models.
Problem-Solving Mindset: An analytical and curious approach to tackling complex challenges.
Educational Background: Currently pursuing or recently graduated with a degree in Computer Science, AI, Data Science, or a related technical field.
Brownie Points For (Preferred Skills)
Experience with the Hugging Face ecosystem (Transformers, Datasets, Tokenizers).
A portfolio of personal or academic projects on GitHub showcasing your AI/ML skills.
Familiarity with vector databases (e.g., Pinecone, ChromaDB).
Shubham Vishwakarma
Full Stack Developer - Averlon
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