GenAI & ML Solutions Architect - Cloud AI Strategist

Amazon Web Services (AWS); Austin (TX); 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

AWS is seeking a Machine Learning Solutions Architect (ML SA) to serve as the SME for AMERICAS design of ML-powered solutions using AWS AI/ML services. You will collaborate with ISVs to enable large-scale use cases, design ML pipelines, and promote AWS AI/ML platforms across customer engagements. Travel up to 50% may be required.

You will work with service teams to gather customer feedback, write white papers, and produce reference implementations to help customers leverage AI/ML on AWS.

Qualifications

• 2+ years of design, implementation, or consulting in applications and infrastructures experience.
• 4+ years of experience in software development, cloud computing, systems engineering, infrastructure, security, networking, or data & analytics.
• Experience working within software development or Internet-related industries (preferred).

Responsibilities

• Work with customers’ development and data science teams to deeply understand their needs and design AWS cloud-based solutions.
• Partner with SAs, Sales, and AI/ML Service teams to accelerate adoption and revenue for SageMaker and GenAI services.
• Evangelize AWS ML services and share best practices via blogs, whitepapers, reference architectures, and events.
• Develop and support an internal AWS GenAI knowledge network in the AMERICAS.

Skills

Design experience

Cloud computing

Software development

Data & analytics

Job description

AWS is seeking a Machine Learning Solutions Architect (ML SA) to serve as the SME for AMERICAS design of ML-powered solutions using AWS AI/ML services. You will collaborate with ISVs to enable large-scale use cases, design ML pipelines, and promote AWS AI/ML platforms across customer engagements. Travel up to 50% may be required.

You will work with service teams to gather customer feedback, write white papers, and produce reference implementations to help customers leverage AI/ML on AWS.