Rest The Case Services Pvt Ltd
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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).
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Founded in 2011, Poshmark started with a simple yet powerful idea in Manish Chandra's garage. Along with co-founders Tracy Sun, Gautam Golwala, and Chetan Pungaliya, Chandra envisioned a platform that would revolutionize how people buy and sell fashion. The inspiration came from seeing the potential of the iPhone 4 to create meaningful connections in the shopping experience.
What They Do
Poshmark is not just another e-commerce platform – it's a social marketplace that brings together shopping and community. Think of it as a place where social media meets shopping, allowing users to buy, sell, and discover fashion, home goods, and accessories. With over 80 million users , the platform has become a go-to destination for both casual sellers and entrepreneurial individuals looking to build their own digital boutiques.
Growth & Achievements
- Started as a fashion-only platform and successfully expanded into home goods and electronics
- Raised over $160 million in venture funding
- Achieved a successful IPO in January 2021
- Recently launched innovative features like AI-powered visual search and livestream shopping
- Built a vibrant community of millions of buyers and sellers across the country
Today, under CEO Manish Chandra's leadership, Poshmark continues to innovate in the social commerce space, blending technology with community to create a unique shopping experience. The platform's success story is a testament to how combining social connections with commerce can create a powerful marketplace that resonates with modern consumers.
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