About The Role
We are seeking a highly skilled
Gen AI & Data Science Lead with strong expertise in
NLP, Generative AI, Machine Learning, and Python. The ideal candidate will lead AI/ML initiatives, build intelligent solutions using advanced NLP and GenAI models, and drive data science strategy across the organization. This role requires strong technical leadership, hands-on modeling experience, and the ability to guide teams in designing and deploying scalable AI solutions.
Key Responsibilities
- Lead end-to-end development of Generative AI and NLP solutions, including model design, training, fine-tuning, and deployment.
- Architect and implement machine learning models, ensuring accuracy, scalability, and performance.
- Build and maintain pipelines for data processing, model training, inference, and production deployment.
- Work with large-scale datasets and develop advanced NLP models (LLMs, transformers, embeddings, RAG systems, etc.).
- Evaluate and integrate modern GenAI frameworks (LangChain, LlamaIndex, HuggingFace, etc.).
- Collaborate with product, engineering, and business teams to identify AI-driven opportunities and deliver high-impact solutions.
- Lead and mentor a team of data scientists, ML engineers, and analysts.
- Stay updated with the latest advancements in LLMs, generative AI, deep learning, and MLOps practices.
- Conduct POCs, research new AI capabilities, and drive innovation culture across projects.
- Present insights, model performance, and solution recommendations to leadership and stakeholders.
Mandatory Skills
- Strong hands-on experience in Natural Language Processing (NLP)
- Expertise in Generative AI, LLMs, and transformer-based architectures
- Solid understanding of Machine Learning (ML) algorithms and model lifecycle
- Advanced proficiency in Python and ML libraries (TensorFlow, PyTorch, HuggingFace, Scikit-learn, etc.)
- Experience building AI models for text generation, summarization, classification, NER, sentiment analysis, and conversational AI
- Familiarity with cloud platforms (AWS/Azure/GCP) for AI/ML development
- Strong understanding of data preprocessing, vector databases, embeddings, and RAG frameworks
Preferred / Good-to-Have Skills
- Experience with MLOps: MLflow, Kubeflow, Airflow, Docker, CI/CD automation
- Knowledge of big data technologies (Spark, Databricks)
- Experience deploying AI models in production environments
- Understanding of data engineering workflows
- Experience in leading cross-functional teams and managing AI projects
Skills: machine learning,data science,nlp,data,ml
