AI/ML Associate Manager

Role Overview

As an AI/ML Associate Manager, you will design, develop, and deploy advanced Artificial Intelligence (AI) and Machine Learning (ML) solutions that address complex business challenges. You will leverage cloud AI services, Generative AI technologies, and modern MLOps practices to build scalable, production-ready AI systems. This role requires expertise in model development, data engineering, and AI platform capabilities to support enterprise-wide AI adoption.

Key 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.

Basic Qualifications

• 6-9 years of experience in Artificial Intelligence, Machine Learning, Data Science, Data Engineering, or related fields.
• Hands-on experience developing and deploying AI/ML solutions in enterprise environments.
• Strong experience with Python and popular AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar technologies.
• Experience working with Generative AI, Large Language Models (LLMs), Deep Learning, and related AI technologies.
• Knowledge of cloud-based AI services on Azure, AWS, or Google Cloud Platform.
• Experience building data pipelines and implementing MLOps practices for model deployment and monitoring.
• Strong understanding of data engineering, data preprocessing, and model optimization techniques.

Preferred Qualifications

• Experience fine-tuning and deploying Generative AI and foundation models for business use cases.
• Knowledge of Retrieval-Augmented Generation (RAG), vector databases, embeddings, and AI agent frameworks.
• Experience with containerization technologies such as Docker and orchestration platforms such as Kubernetes.
• Familiarity with edge AI, distributed computing, and high-performance computing (HPC) environments.
• Experience with AI observability, model monitoring, and production support processes.
• Strong analytical, problem-solving, and stakeholder management skills.
• Relevant certifications in Artificial Intelligence, Machine Learning, Data Science, or Cloud Technologies are preferred.