Data Scientist (2+ Yrs Exp)

We are looking for a highly skilled Data Scientist with 2-3 years of experience who has worked extensively with Large Language Models (LLMs) and retrieval methods. You will be responsible for building, fine-tuning, and deploying AI models to solve complex NLP challenges. The ideal candidate has hands-on experience in finetuning, optimizing, and implementing LLM-based solutions in real-world applications.

Typical work week look like:-

• Research, fine-tune, and deploy LLMs and other Transformer-based architectures for various NLP tasks.
• Design and implement custom training pipelines for domain-specific models.
• Optimize model performance, including prompt engineering, quantization, distillation, and retrieval-augmented generation (RAG).
• Work with Hugging Face, OpenAI, and other open source foundational model APIs to build scalable solutions.
• Develop and maintain data pipelines for model training and evaluation.
• Collaborate with engineering teams to integrate AI models into production systems.
• Conduct experiments and analyze results to continuously improve model accuracy and efficiency.
• Stay up to date with cutting-edge advancements in generative AI, LLMs, and NLP.

Our ideal candidate should have:-

• 2+ years of hands-on experience in data science, with a focus on NLP and deep learning.
• Strong knowledge of Transformer architectures (BERT, GPTs, T5, LLaMA, etc.).
• Experience in fine-tuning and deploying LLMs using PyTorch, TensorFlow.
• Proficiency with Hugging Face Transformers, LangChain, OpenAI API, or similar frameworks.
• Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow).
• Experience with vector databases (Pinecone, ChromaDB) and retrieval-augmented generation (RAG).
• Knowledge of cloud platforms (AWS, GCP, Azure) and ML model deployment strategies.
• Familiarity with MLOps practices, including model monitoring, versioning, and CI/CD for ML.
• Strong problem-solving skills and ability to work in a fast-paced environment.

Preferred Qualifications

• Experience with multi-modal models (e.g., Whisper, DALL·E).
• Exposure to LLM inference optimization techniques like quantization, pruning, and knowledge distillation.
• Experience working on chatbots, conversational AI, or document intelligence solutions.

What you can expect from ORI:-

• Opportunity to work on cutting-edge AI/ML projects.
• A collaborative, innovation-driven work environment.
• Passion & happiness in the workplace with great people & open culture with amazing growth opportunities.
• An ecosystem where leadership is fostered which builds an environment where everyone is free to take necessary actions to learn from real experiences.
• Freedom to pursue your ideas and tinker

If you are passionate about LLMs and pushing the boundaries of AI, we’d love to hear from you!