Data Scientist - NLP/LLM

Job Description

Job Description We are looking for an experienced Data Scientist with expertise in Large Language Models (LLMs), Chatbots, Computer Vision (CV), and Statistical Modeling. The ideal candidate should have a strong background in Machine Learning, Deep Learning, NLP & Computer Vision, along with experience in developing and deploying models at scale. Exposure to FastAPI, Flask, and cloud-based tools will be a significant advantage. Key Responsibilities Design, develop, and optimize machine learning models for various applications, including LLMs, chatbots, and computer vision. Work on NLP-based conversational AI solutions, including chatbots and virtual assistants. Implement computer vision models for image recognition, object detection, and classification tasks. Develop statistical models for data-driven decision-making, forecasting, and pattern recognition. Optimize model performance, conduct hyperparameter tuning, and improve inference efficiency. Deploy ML models using FastAPI, Flask, or similar frameworks. Work with cloud platforms (AWS, GCP, Azure) for model training, deployment, and scaling. Collaborate with data scientists, software engineers, and product teams to integrate ML models into production environments. Stay updated with the latest advancements in ML, deep learning, and AI research. Required Skills & Qualifications 3+ years of experience in machine learning, deep learning, NLP, or computer vision. Strong proficiency in Python and ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers, OpenAI, etc. Experience with LLMs, chatbot development, and fine-tuning transformer-based models. Hands-on experience in computer vision using OpenCV, YOLO, or similar frameworks. Proficiency in statistical modeling, regression analysis, and probabilistic models. Experience in building and deploying APIs using FastAPI, Flask, or Django. Familiarity with MLOps, model monitoring, and optimization. Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes). Strong problem-solving skills and ability to work in a fast-paced environment. Preferred Skills (Nice To Have) Experience with multi-modal LLMs, where both text and image inputs are used for model training and inference. Experience with vector databases (FAISS, Pinecone, ChromaDB) for LLM-based applications. Knowledge of graph-based ML models for recommendation systems. Exposure to real-time ML model deployment and inference optimization. Understanding of Reinforcement Learning (RL) techniques for chatbots. (ref:hirist.tech)