AI / ML Engineer

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 (LLMs) Good to have skills : NA Minimum 3 year(s) of experience is required Educational Qualification : 15 years full time education

Summary: As an AI / ML Engineer, a typical day involves designing and building advanced applications and systems that leverage artificial intelligence technologies and cloud-based AI services. The role requires managing end-to-end application pipelines, ensuring solutions are production-ready and scalable. The engineer integrates generative AI models into various projects, which may include deep learning frameworks, neural network architectures, conversational agents, and image processing techniques. Collaboration with cross-functional teams to align technical implementations with project goals is a key aspect of daily activities, fostering innovation and continuous improvement in AI-driven solutions.

Roles & Responsibilities:

• Expected to perform independently and become an SME.
• Required active participation/contribution in team discussions.
• Contribute in providing solutions to work related problems.
• Collaborate with stakeholders to understand requirements and translate them into technical solutions.
• Continuously evaluate and optimize AI models and system performance to meet quality standards.
• Document technical designs, processes, and best practices to support knowledge sharing.
• Assist junior team members by providing guidance and support to enhance their technical skills.

Professional & Technical Skills:

• Must To Have Skills: Proficiency in Large Language Models (LLMs).
• Experience with designing and deploying AI applications using cloud AI services and on-premises infrastructure.
• Strong understanding of generative AI model integration and application development.
• Familiarity with deep learning techniques, neural networks, and chatbot development.
• Ability to develop and maintain production-quality AI pipelines ensuring scalability and reliability.

Additional Information