Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : Large Language Models
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary: As an LLM Engineer, you will develop applications and systems that utilize AI to improve performance and efficiency. Your typical day will involve working with Machine Learning, Natural Language Processing, Deep Learning, Neural Networks, Chatbots to create innovative solutions. Roles & Responsibilities: - Design and develop scalable and efficient AI-based applications and systems using Large Language Models, deep learning, neural networks, chatbots, and natural language processing. - Collaborate with cross-functional teams to identify and prioritize AI use cases, and develop solutions that meet business requirements. - Implement and maintain AI models and algorithms, and ensure their accuracy, reliability, and scalability. - Develop and maintain AI infrastructure, including data pipelines, model training and deployment pipelines, and monitoring and logging systems. - Stay updated with the latest advancements in AI and machine learning, and integrate innovative approaches for sustained competitive advantage. Professional & Technical Skills: - Must To Have Skills: Experience & Proficiency in Large Language Models - Strong understanding of deep learning, neural networks, chatbots, and natural language processing. - Experience with AI infrastructure, including data pipelines, model training and deployment pipelines, and monitoring and logging systems. - Proficiency in programming languages such as Python, Java, or C++. - Experience with cloud platforms such as AWS, Azure, or GCP. - Experience with containerization technologies such as Docker and Kubernetes. - Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms - Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity Additional Information: - A 15 years full time education is required