4.0 - 9.0 years

20 - 35 Lacs

Pune

Hybrid

Key Skills: Data Science, Machine Learning, NLP, Generative AI, LLM, Transformer Networks, GANs, VAEs, Prompt Engineering, Model Development, MarkLogic (preferred), Cloud-native models, Model Deployment, Data Pipelines Roles & Responsibilities: Apply deep learning and generative modeling techniques to develop LLM solutions in AI, especially in the field of Natural Language Processing (NLP). Work with various LLM technologies and Transformer Encoder Networks to enhance NLP capabilities. Design and implement state-of-the-art generative models for tasks such as text generation, text completion, language translation, and document summarization. Utilize expertise in machine learning, focusing on generative models like GANs, VAEs, and transformer-based architectures. Develop and optimize model development, model serving, and training/re-training techniques in data-sparse environments. Apply prompt engineering techniques for developing instruction-based LLMs. Collaborate with SAs and cross-functional teams to identify business requirements and deliver solutions that meet customer needs. Stay updated with the latest advancements in generative AI and LLM technologies. Evaluate and preprocess large-scale datasets, ensuring data quality and integrity, and develop data pipelines for model training and evaluation. Articulate model behavior analysis and hallucination effects to business stakeholders. Develop guardrails for LLMs, leveraging both open-source and cloud-native models. Collaborate with software engineers to deploy and optimize generative models in production environments. Mentor junior data scientists and contribute to the growth of the data science team. Experience Requirement: 4-10 years of experience working in Data Science, Machine Learning, and especially NLP technologies. Experience with LLM technologies and solid understanding of Transformer Encoder Networks. Proven experience with generative models, including GANs, VAEs, and transformer-based architectures. Familiarity with model development, training/re-training techniques, and deployment in data-sparse environments. Strong understanding of prompt engineering techniques for LLMs. Experience with data preprocessing and building data pipelines for generative models. Ability to explain model behaviors, hallucination effects, and behavioral analysis techniques to stakeholders. Experience with developing guardrails for LLMs using open-source or cloud-native models. Exposure to MarkLogic is a plus. Education: Any Graduation.

Posted 19 hours ago

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