AI/ Data Scientist Lead

Key Responsibilities

1. Design, develop, and deploy end-to-end machine learning and AI models for diverse business use cases.
2. Apply advanced deep learning architectures (CNNs, RNNs, Transformers, etc.) for solving complex problems in vision, text, and structured/unstructured data.
3. Develop and fine-tune NLP models for text classification, sentiment analysis, information extraction, conversational AI, and semantic search.
4. Explore and implement Generative AI (LLMs, diffusion models, prompt engineering, fine-tuning, RAG pipelines, etc.) to enhance existing AI/ML capabilities.
5. Collaborate with product, engineering, and business stakeholders to translate requirements into AI-driven solutions.
6. Drive model performance optimization (scalability, latency, explainability, accuracy).
7. Lead and mentor junior data scientists, providing technical guidance and best practices.
8. Stay up to date with emerging AI/ML and GenAI frameworks, tools, and research trends.

Required Skills & Experience

1. 5+ years of experience in Data Science, AI/ML, and related fields.
2. Strong proficiency in Python, R, or similar languages with expertise in data science libraries (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, Hugging Face).
3. Proven experience in designing and deploying ML/DL models in production.
4. Deep knowledge of NLP techniques: embeddings, Transformers, BERT/GPT-style models, seq2seq, text generation, entity recognition.
5. Hands-on exposure to Generative AI (e.g., OpenAI, Hugging Face, LangChain, vector databases, RAG, LLM fine-tuning).
6. Strong knowledge of cloud platforms (AWS, Azure, GCP) for ML/AI model deployment.
7. Solid understanding of MLOps practices (model versioning, monitoring, CI/CD pipelines).
8. Strong analytical, problem-solving, and communication skills.
9. Ability to work in a fast-paced, collaborative environment.