Description

Design, develop, and deploy machine learning, deep learning, and generative AI models for healthcare and business applications.

Responsibilities

• Build and optimize feature engineering pipelines and data preprocessing workflows for structured and unstructured datasets.
• Implement NLP solutions for text classification, entity extraction, summarization, and information retrieval.
• Design and fine-tune Large Language Models (LLMs) and transformer-based architectures, applying transfer learning and prompt engineering techniques.
• Develop AI-driven document intelligence solutions using LayoutLM, Donut, and Table Transformers for key-value extraction.
• Support MLOps and model deployment, including Docker-based packaging, cloud deployment, and performance monitoring.

Required Skills

• 5+ years of hands-on experience in AI/ML model development and deployment.
• Proficiency in Python with PyTorch, TensorFlow, Scikit-Learn, Pandas, and NumPy.
• Experience with NLP libraries such as Hugging Face Transformers, spaCy, and NLTK.
• Hands-on experience with LLM fine-tuning, prompt engineering, and transformer-based models.
• Knowledge of cloud platforms (AWS/Azure), Docker, and ML deployment workflows.
• Experience with SQL/NoSQL databases and data manipulation at scale.
• Bachelor's degree in Computer Science or related field.

Preferred Skills

• Experience with RAG architectures, vector databases, embeddings, and semantic search.
• Familiarity with LLM alignment techniques (RLHF, DPO, PPO, KTO).
• Experience with computer vision or document AI models for OCR and document understanding.

Key Skills

Education

Bachelor's degree