Delivery Consultant - AI/ML, AWS Professional Services WWPS Healthcare and Life Science
About the Role
Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intelligence (AI) systems? Want to help the largest global enterprises derive business value through the adoption and automation of Generative AI (GenAI)? Excited by using massive amounts of disparate data to develop AI/ML models? Eager to learn to apply AI/ML to a diverse array of enterprise use cases? Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades - pioneering and shaping the world’s AI technology? The Amazon Web Services Professional Services (ProServe) 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
Qualifications
- 3+ years of software development, or 3+ years of scripting language experience
- 3+ years of building machine learning and generative AI models for business application experience
- Experience with cloud services related to machine learning (e.g., Amazon SageMaker) and generative AI applications
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 6li> Domain expertise in healthcare and life sciences
Pay
The base salary range for this position varies by location:
- USA, CA, San Francisco: $151,000.00 - $204,300.00 USD annually
- USA, CO, Denver: $131,300.00 - $177,600.00 USD annually
- USA, GA, Atlanta: $131,300.00 - $177,600.00 USD annually
- USA, IL, Chicago: $131,300.00 - $177,600.00 USD annually
- USA, NJ, Jersey City: $144,500.00 - $195,400.00 USD annually
- USA, NY, New York: $144,500.00 - $195,400.00 USD annually
- USA, TX, Dallas: $131,300.00 - $177,600.00 USD annually
- USA, VA, Arlington: $131,300.00 - $177,600.00 USD annually
- USA, VA, Herndon: $131,300.00 - $177,600.00 USD annually
- USA, WA, Seattle: $131,300.00 - $177,600.00 USD annually
Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits, including health insurance, 401(k) matching, paid time off, and parental leave.
Application deadline: Sep 27, 2026