GenAI & ML Delivery Consultant

Amazon Web Services (AWS); Denver (CO); On-site; USD 131,000 - 178,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Web Services, Inc. is seeking a Delivery Consultant in ML/GenAI to work with customers on designing, implementing, and managing AWS AI/ML and GenAI solutions that meet business goals. You will guide migrations, architecture, and best practices across the ML project lifecycle.

The role involves collaborating with Applied Science, DevOps, Data Engineering and Cloud Infrastructure teams, mentoring peers, and traveling to customer sites as needed to ensure successful cloud journeys.

Qualifications

• 3+ years of software development experience.
• 3+ years of building machine learning and generative AI models for business applications.
• Experience with cloud services related to machine learning (e.g., Amazon SageMaker) and generative AI applications.

Responsibilities

• Implement end-to-end AI/ML and GenAI projects across data prep, modeling, deployment and monitoring.
• Design scalable ML pipelines for high-performance and secure workloads.
• Develop MLOps practices using AWS services and GenAI capabilities.
• Collaborate with cross-functional teams to operationalize data and AI/ML models.
• Serve as a trusted advisor on AI/ML and cloud architectures for customers.
• Share knowledge through mentoring, training, and creating reusable artifacts.
• Ensure solutions meet industry standards and support AI/GenAI adoption strategies.

Skills

Software development

ML/GenAI models

AWS SageMaker

Tools

SageMaker

Bedrock

EC2

ECS

EKS

Job description

Amazon Web Services, Inc. is seeking a Delivery Consultant in ML/GenAI to work with customers on designing, implementing, and managing AWS AI/ML and GenAI solutions that meet business goals. You will guide migrations, architecture, and best practices across the ML project lifecycle.

The role involves collaborating with Applied Science, DevOps, Data Engineering and Cloud Infrastructure teams, mentoring peers, and traveling to customer sites as needed to ensure successful cloud journeys.