Responsibilities :

- Must have 10 + years of experience working in Data science, Machine learning and especially NLP technologies.

- Solid understanding of Model development, model serving, training/re-training techniques in a data sparse environment.

- Must have experience with Agentic AI frameworks LangGraph, LlamaIndex, MCP etc.

- Expert in using paid (OpenAI on Azure) and open source LLMs

- Strong understanding of Agents development.

- Experience with Python programming language in a must.

- Ability to develop Python code as needed and train the Developers based on business needs.

- Experience with AWS / Azure ecosystem is a must.

- Preferable candidate should possess Pharma R&D background

- Strong understanding of cloud native application development in AWS / Azure.

- Able to apply deep learning and generative modeling techniques to develop LLM solutions in the field of Artificial Intelligence.

- Utilize your extensive knowledge and expertise in machine learning (ML) with a focus on generative models, including but not limited to generative adversarial networks (GANs), variational autoencoders (VAEs), and transformer-based architectures.

- Very good understanding of Prompt engineering techniques in developing Instruction based LLMs.

- Must be able to design, and implement state-of-the-art generative models for natural language processing (NLP) tasks such as text generation, text completion, language translation, and document summarization.

- Work with SAs and collaborate with cross-functional teams to identify business requirements and deliver solutions that meet the customer needs.

- Passionate to learn and stay updated with the latest advancements in generative AI and LLM.

- Nice to have -contributions to the research community through publications, presentations, and participation in relevant conferences or workshops.

- Evaluate and preprocess large-scale datasets, ensuring data quality and integrity, and develop data pipelines for training and evaluation of generative models.

- Ability to articulate to business stakeholders on the hallucination effects and various model behavioral analysis techniques followed.

- Exposure to developing Guardrails for LLMs both with open source and cloud native models.

- Collaborate with software engineers to deploy and optimize generative models in production environments, considering factors such as scalability, efficiency, and real-time performance.

- Nice to have- provide guidance to junior data scientists, sharing expertise and knowledge in generative AI and LLM, and contribute to the overall growth and success of the data science team.

- Expert in RDBMS database

- Experience on Marklogic / No SQL database

- Experience on Elastic search