AI/ML Tech Lead With AWS Tools

Role Description: We are looking for an experienced AI/ML Tech Lead to drive end-to-end delivery of advanced AI and machine learning solutions across our enterprise platforms. In this role, you will lead the architecture, development, and deployment of production-grade ML models, GenAI applications, and scalable data processing pipelines using AWS and modern data engineering frameworks. Key Responsibilities • Lead the full lifecycle of AI/ML solution delivery, from discovery and model selection to production deployment and performance optimization. • Architect and implement solutions using AWS Bedrock, SageMaker, Textract, Lambda, ECS, and EKS. • Develop ML and GenAI models using Python, including data preprocessing, feature engineering, and algorithm selection. • Build scalable data pipelines integrating unstructured and structured data using AWS Glue, Lambda, Step Functions, and Databricks. • Design and manage Docker-based containerized applications and deploy them using AWS ECS/EKS. • Work with Data Lake architectures (S3, Lake Formation) and integrate data from Aurora and MongoDB. • Manage training datasets, labeling workflows, model retraining, and automated ML pipelines. • Collaborate with engineering, cloud, and product teams to translate business requirements into scalable ML architectures. • Ensure solutions meet enterprise standards for security, performance, reliability, and cost optimization. • Mentor ML engineers and data engineers, driving best practices in cloud engineering, MLOps, and AI development. Required Skills & Experience • 4+ years of hands-on experience in machine learning, AI engineering, or data science. • Strong proficiency with Python, ML frameworks, and building end-to-end ML solutions. • Deep experience with AWS AI/ML services, including Bedrock, SageMaker, Textract, and Lambda. • Expertise in containerization with Docker and orchestration using ECS/EKS. • Experience designing solutions using Data Lakes, Databricks notebooks, and scalable ETL pipelines. • Practical experience with Aurora (MySQL/PostgreSQL) and MongoDB. • Solid knowledge of cloud security, IAM permissions, VPC networking, and MLOps practices. • Strong communication, technical leadership, and ability to collaborate across teams.