AI/ML Associate Manager

Overview

Responsibilities

• Design and develop AI and Machine Learning solutions using cloud-native AI services and modern AI frameworks
• Build and maintain scalable data pipelines to support model training, deployment, monitoring, and production operations
• Implement DevOps and MLOps practices to enable efficient model lifecycle management and continuous delivery
• Customize, fine-tune, and deploy Generative AI, Large Language Models (LLMs), and Deep Learning models based on business requirements
• Develop AI solutions that operate across cloud environments, edge devices, and high-performance computing (HPC) infrastructures
• Evaluate model performance and demonstrate the business value, accuracy, and effectiveness of AI solutions
• Conduct research and development activities to assess emerging AI technologies, algorithms, and modeling approaches
• Work with large-scale structured and unstructured datasets, applying data preparation and feature engineering techniques to improve model outcomes
• Design and implement efficient data, model, and knowledge storage solutions to support AI applications and retrieval capabilities
• Collaborate with data engineers, architects, and business stakeholders to deliver scalable and production-ready AI solutions
• Ensure AI solutions follow security, governance, and Responsible AI standards throughout the development lifecycle

Requirements

• Expertise in model development, data engineering, and AI platform capabilities
• Experience with cloud AI services and modern AI frameworks
• Proven ability to implement DevOps and MLOps practices
• Experience in customizing, fine-tuning, and deploying Generative AI, Large Language Models (LLMs), and Deep Learning models
• Ability to develop AI solutions that operate across cloud environments, edge devices, and high-performance computing (HPC) infrastructures
• Experience in evaluating model performance and demonstrating business value, accuracy, and effectiveness of AI solutions
• Ability to conduct research and development activities to assess emerging AI technologies, algorithms, and modeling approaches
• Experience in working with large-scale structured and unstructured datasets, applying data preparation and feature engineering techniques to improve model outcomes
• Ability to design and implement efficient data, model, and knowledge storage solutions to support AI applications and retrieval capabilities
• Experience in collaborating with data engineers, architects, and business stakeholders to deliver scalable and production-ready AI solutions
• Ability to ensure AI solutions follow security, governance, and Responsible AI standards throughout the development lifecycle