Generative AI Engineer

2 months ago


bangalore, India L&T Technology Services Full time

About the Company :
We are seeking a talented and experienced Generative AI (GenAI) Data Scientist to join our growing team. In this role, you will play a vital role in developing and deploying cutting-edge GenAI models for various applications, with a specialization in fine-tuning Generative Pre-trained Transformers (GPTs) using the Retrieval-Augmented Generation (RAG) method.

Responsibilities :
Collaborate with engineers and researchers to design, develop, and implement GenAI models.
Participate in all stages of the GenAI lifecycle, from data collection and pre-processing to model training, evaluation, and deployment.
Develop expertise in fine-tuning GPTs using the RAG method for specific tasks.
Design and implement evaluation metrics to assess the quality, effectiveness, and fairness of GenAI models.
Work with domain experts to ensure generated outputs align with real-world needs and business objectives.
Stay up-to-date on the latest advancements in GenAI research and actively participate in knowledge sharing within the team.

Qualifications :
Bachelor’s and Master's degree in Computer Science, Artificial Intelligence, or a related field (or equivalent experience).
2+ years of experience working with AI. A good hands-on understanding of Generative AI models, preferably with a focus on text-based generation.
Strong understanding of deep learning architectures, particularly transformers like GPT-n.
Proven experience in fine-tuning pre-trained models with techniques like RAG.
Proficiency in Python programming languages and libraries like TensorFlow, PyTorch, and Hugging Face Transformers.
Experience with data analysis, manipulation, and visualization techniques.
Excellent communication and collaboration skills to work effectively in a cross-functional team.
A passion for innovation and a desire to push the boundaries of what's possible with AI.

Preferred Skills :
Experience working on real-world GenAI projects and deploying models to production.
Knowledge of fairness and bias considerations in AI development.
Experience with Azure stack.



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