Senior AI/ML Cloud Delivery Lead

Amazon Web Services (AWS); Seattle (WA); On-site; USD 154,000 - 208,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Job summary

Amazon Web Services, Inc. in Seattle is seeking a Senior AI/ML Delivery Consultant to design, implement, and manage GenAI and ML applications on AWS for customers, guiding architecture and best practices.

You will gather requirements, propose training and deployment strategies, and lead project delivery with a focus on secure, scalable solutions, while mentoring peers and sharing reusable artifacts across teams.

Qualifications

• 5+ years of machine learning, statistical modeling, data mining, and analytics techniques experience.
• 5+ years of data querying languages (SQL) and scripting (Python) experience.
• 3+ years of customer-facing work, engaging with customer executives or partners to solve business problems with advanced technologies.
• 4+ years of Data & AI related technologies, including AI/ML, GenAI, Analytics, Database, and Storage experience.
• 3+ years of coding, data querying languages (SQL) and scripting (Python).

Responsibilities

• Designing, implementing, and building complex, scalable, and secure GenAI and ML applications on AWS.
• Providing technical guidance and implementation support throughout project delivery with a focus on AWS AI/ML services.
• Collaborating with customer stakeholders to gather requirements and propose training, building, and deployment strategies.
• Acting as a trusted advisor to customers on industry trends and emerging technologies.
• Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts.

Skills

ML experience

SQL

Python

Customer facing

Data & AI tech

Tools

AWS services

LLMs in production

GPUs/AI hardware

Job description

Amazon Web Services, Inc. in Seattle is seeking a Senior AI/ML Delivery Consultant to design, implement, and manage GenAI and ML applications on AWS for customers, guiding architecture and best practices.

You will gather requirements, propose training and deployment strategies, and lead project delivery with a focus on secure, scalable solutions, while mentoring peers and sharing reusable artifacts across teams.