Delivery Consultant - AI/ML, AWS Professional Services WWPS Life Science

About the role

The AWS Professional Services team is seeking a skilled ML Engineer to join our team as a Delivery Consultant at Amazon Web Services (AWS).

Responsibilities

• Implementing end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring
• Designing and implementing machine learning pipelines that support high-performance, reliable, scalable, and secure ML workloads
• Designing scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable
• Collaborating with cross-functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models
• Serving as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures
• Sharing knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts
• Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML, GenAI, and cloud adoption strategies

Requirements

• Experience with AI/ML technologies
• 3+ years of building machine learning and generative AI models for business application experience
• 3+ years of customer-facing work, engaging with customer executives, technologists or partners to solve business problems with advanced technologies experience
• Experience with cloud services related to machine learning (e.g., Amazon SageMaker) and generative AI applications
• 3+ years of coding, data querying languages (e.g. SQL), and scripting languages (e.g. Python)

Preferred Qualifications

• Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies
• Knowledge of AWS services including SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch and AWS certifications
• 2+ years of experience with design, deployment, and evaluation of AI agents and orchestration approaches; experience with open source frameworks like LangChain, LangGraph, LlamaIndex, and/ or similar tools
• 3+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience using PyTorch or TensorFlow
• Experience building ML pipelines with MLOps best practices, including: data preprocessing, distributed & GPU training, model deployment, monitoring, and retraining; experience with container and CI/CD pipelines
• Domain expertise in healthcare and life sciences