Data Scientist

Key Responsibilities:

• Fine-tune LLMs using techniques like LoRA and QLoRA
• Evaluate and enhance RAG (Retrieval-Augmented Generation) pipelines for groundedness, accuracy, and relevance
• Implement transfer learning and transformer architectures in model development
• Validate model accuracy and performance using appropriate metrics
• Collaborate with product teams, communicate insights to senior leadership, and contribute to problem-solving sessions
• Maintain an experimental mindset, explore new approaches continuously, and identify/integrate relevant data sources to create meaningful datasets
• Automate data collection and preprocessing for both structured and unstructured data
• Handle large-scale data to feed analytical and predictive models
• Build and optimize machine learning and deep learning models, particularly in NLP solutions

Qualifications Required:

• Bachelors degree in a quantitative field (Computer Science, Engineering, Physics, Mathematics, Operations Research) or equivalent experience
• 1-4 years of hands-on experience in Generative AI and NLP
• Previous experience in startups or high-growth environments is a plus

Technical Skills Required:

• Deep expertise in NLP techniques such as text generation, sentiment analysis, NER, and language modeling
• Hands-on experience with LLMs and RAG pipelines
• Proficiency in neural network frameworks like TensorFlow and PyTorch
• Familiarity with transformer architecture and transfer learning
• Fluency in at least one programming language: Python, R, or Julia
• Experience with Generative AI libraries like Hugging Face, OpenAI, etc.
• Strong foundation in ML algorithms including supervised, unsupervised, reinforcement learning, Bayesian inference

- Skills in Fine Tuning, Transfer Learning, Pytorch, Tensorflow, and analytical abilities.,