AI/ML Architect

Summary

Join our team as an AI/ML Architect (AWS) and leverage your expertise in traditional Machine Learning and cutting-edge Artificial Intelligence, with a focus on Generative AI. This remote position requires deep knowledge of AWS and strong communication skills. You will develop and implement automation and DevOps methodologies, design automation strategies, engage with clients, and maintain technical documentation. The role demands experience with machine learning frameworks, generative AI architectures, and AWS services. A strong background in cloud migrations and IT transformations is essential.

Requirements

• Experienced with machine learning frameworks(TensorFlow, PyTorch) and libraries (e.g., scikit-learn)
• Proven hands-on experience with generative AI architectures, including design, training, and customization for LLM in text-to-text, image-to-text, and/or text-to-image projects
• Implement and customize generative AI architectures and approaches such as finetuning transformer based LLMs using PEFT methods like LoRA, QLoRAetc
• Expertise in public cloud services, particularly in AWS
• Experienced  working with Sagemaker, Bedrock and other AWS AI and Machine learning services
• Experience with AWS managed services and understanding of cloud-based messaging/stream processing systems are critical
• AWS/ Azure Cloud Professional level certification in AI/ML, Architecture and Data
• 10+ years of experience in customer-facing software/technology or consulting
• 5+ years of experience with “on-premises to cloud” migrations or IT transformations
• 5+ years of experience building, and operating solutions built on AWS (ideally) or Azure/GCP
• Technical degree: Computer Science, software engineering or related

Responsibilities

• Develop and implement automation and DevOps methodologies, including CI/CD, Infrastructure as Code (IaC), and containerization, to establish a scalable Machine Learning and Artificial Intelligence infrastructure
• Design and execute automation strategies, encompassing DevOps pipelines, scripting, and Terraform-based Infrastructure as Code
• Engage actively in client sessions to understand and address their needs
• Prepare and maintain detailed technical documentation