Tech Lead
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About The Position
The Tech Lead position at Tech Mahindra is a pivotal role that requires a seasoned professional with over 10 years of experience in the technology sector, particularly in leading AI projects. The ideal candidate will have a strong background in Generative AI and experience working within an onshore-offshore model. A Master's degree in Computer Science is mandatory, ensuring that the candidate possesses a solid theoretical foundation in the field. The role demands hands-on implementation experience with large language model frameworks and tools such as Langchain, Llamaindex, and Flowise, with at least one year of direct experience. Additionally, the candidate should have a minimum of two years of experience fine-tuning large language models and working with natural language processing (NLP), prompt engineering, vector databases, and retrieval-augmented generation techniques. Candidates should also have substantial experience in exploratory data analysis and feature engineering, particularly with unstructured text data and structured or semi-structured metadata. Proficiency in Python and related machine/deep learning libraries, including Sklearn, Torch, Keras, Spacy, and Pandas, is essential. Experience in chatbot development is preferred, along with familiarity with RAG techniques and their application in AI projects. The position also requires experience in cloud platforms and deploying AI models in production environments, as well as familiarity with NLP libraries and frameworks, particularly Hugging Face Transformers. The candidate should be adept at designing and developing chatbots and virtual assistants, customizing pre-trained models for specific use cases, and integrating applications with various platforms and services through RESTful APIs. Moreover, the candidate should have experience with data pipelines and ETL processes, as well as A/B testing, model tuning, and iterative improvements to enhance chatbot accuracy and user satisfaction. This role is crucial for driving innovation and ensuring the successful implementation of AI solutions within the organization.
