AI / ML Engineer

Role Overview

As an AI / ML Engineer, a typical day involves designing and building advanced applications and systems that leverage artificial intelligence tools and cloud-based AI services. The role requires managing application pipelines that are either cloud-hosted or on-premises, ensuring they meet production-level standards. The engineer integrates generative AI models into solutions and works on diverse technologies such as deep learning, neural networks, chatbots, and image processing. Collaboration with cross-functional teams to align AI capabilities with project goals and continuous refinement of AI-driven applications are key aspects of the daily workflow.

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.
• Maintain and optimize AI application pipelines to ensure reliability and scalability.
• Support junior team members by sharing knowledge and providing guidance.
• Continuously monitor and improve the performance of deployed AI models.

Requirements

• Minimum 3 years of experience in Machine Learning Operations.
• 15 years full time education.
• Experience with cloud platforms and managing AI service integrations.
• Strong understanding of model deployment, monitoring, and lifecycle management.
• Familiarity with containerization and orchestration tools to support scalable AI solutions.
• Ability to troubleshoot and resolve issues in production AI pipelines.
• Knowledge of data preprocessing and feature engineering techniques relevant to AI workflows.

Skills

• Machine Learning Operations
• DevOps
• Deep Learning
• Neural Networks
• Generative AI