GenAI & ML Solutions Architect for ProServe

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

Job summary

Amazon Web Services, Inc. is seeking a skilled Machine Learning Engineer for AWS ProServe to design, evangelize, implement, and scale AI/ML solutions for customers. You will work directly with clients to scope use cases, select models, and drive AI transformations that deliver measurable business impact.

Role requires deep expertise in machine learning, generative AI, and best practices, with a focus on scalable, secure architectures and collaboration with stakeholders across teams.

Qualifications

• 3+ years of cloud architecture and solution implementation experience.
• 5+ years of machine learning, statistical modeling, data mining, and analytics techniques experience.
• Experience defining benchmarks for GenAI model performance.
• Ability to translate complex technical solutions for diverse audiences.

Responsibilities

• Design, implement, and scale AI/ML solutions on AWS tailored to customer needs.
• Develop and deploy ML models and GenAI applications solving real-world problems.
• Collaborate with stakeholders to identify high-value AI/ML use cases and gather requirements.
• Proactively guide on responsible and cost-efficient AI implementation across projects.
• Act as trusted advisor on AI advancements and data source utilization for business impact.
• Mentor teammates and develop reusable AI/ML artifacts.

Skills

Cloud architecture

Machine learning

GenAI

Stakeholder communication

Security clearance

Job description

Amazon Web Services, Inc. is seeking a skilled Machine Learning Engineer for AWS ProServe to design, evangelize, implement, and scale AI/ML solutions for customers. You will work directly with clients to scope use cases, select models, and drive AI transformations that deliver measurable business impact.

Role requires deep expertise in machine learning, generative AI, and best practices, with a focus on scalable, secure architectures and collaboration with stakeholders across teams.