Job Title - DataScience
Location: Noida
Exp - 8-10yrs
Educational Background: Bachelor's degree in computer science, Information Technology, or related field.
Mode of Work- Hybrid
Experience Required - 8+ years
Key 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, cluding 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.
