Generative AI Lead - Python

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

ref : hirist.tech)