Excelacom - Artificial Intelligence/Machine Learning Specialist (5-8 yrs)

Role Overview :

We're on the lookout for a versatile and skilled AI and Machine Learning Specialist to join our dynamic team. Our ideal candidate will bring expertise across various domains, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Conversational Chatbots, Langchain, RASA Chatbot Framework, AWS SageMaker, AWS Bedrock, and general Machine Learning. As a key member of our team, you'll be tasked with the design, implementation, and optimization of advanced AI and machine learning models and systems.

Responsibilities :

1. Participate in fine-tuning pre-trained models and evaluating performance.

2. Assist in designing and implementing NLP and machine learning models.

3. Support the development and integration of RAG, Chatbots, and various business use cases.

4. Help design and implement chatbot functionalities, including conversation flows and dialogue management.

5. Integrate external APIs and services into various applications.

6. Assist in managing SageMaker environments and deploying foundation models using AWS Bedrock.

7. Monitor and optimize model performance, ensuring data security and compliance.

8. Collaborate with senior team members, data scientists, UX designers, and engineers on various projects.

Required Skills :

1. Proficiency in Python and relevant libraries.

2. Understanding of Large Language Models and their architecture.

3. Knowledge of preparing datasets, fine-tuning pre-trained models, and evaluating/improving LLM performance.

4. Familiarity with Retrieval Augmented Generation (RAG) and improving retrieval algorithms for better document selection.

5. Experience with chatbot frameworks (RASA, Dialogflow) for building and training RASA models.

6. Experience in Python framework(Flask/FastAPI)

7. Familiarity with Langchain framework to integrate with various LLMs based on use cases.

8. Proficiency in AWS Services (Sagemaker, Bedrock).

9. Experience with data cleaning/preparation, training machine learning models, evaluating model performance, improving model results, and deploying models.