SageMaker ML Architect: Model Customization & Inference

Socket.dev; New York (NY); On-site; USD 169,000 - 229,000; Full time

Job summary

Amazon seeks a Machine Learning Solutions Architect to lead model customization and inference across the AMERICAS, enabling foundation models, custom training, and scalable deployment on AWS.

You will design end-to-end ML architectures spanning data prep, distributed training, fine-tuning, and inference optimization, working with SageMaker AI and HyperPod to deliver scalable, cost-efficient solutions for diverse customers.

Qualifications

• 3+ years of specific technology domain areas experience
• 3+ years of design, implementation, or consulting in applications and infrastructures experience
• 5+ years of IT development or implementation/consulting in the software or Internet industries experience

Responsibilities

• Partner with customers to deeply understand business objectives, architect solutions leveraging AWS AI/ML services with model customization and inference optimization
• Serve as SME on model customization and inference patterns across SageMaker AI and SageMaker HyperPod
• Drive adoption across the AMERICAS to accelerate pipeline generation, opportunity progression, and revenue attainment
• Author technical blogs and reference architectures; present at events to establish AWS leadership in model customization and inference
• Capture customer signals and feed improvements back to service teams to influence the product roadmap
• Build and scale an internal ML community across the AMERICAS for knowledge sharing

Skills

Cloud computing

Software development

Systems engineering

Data & analytics

IT development

Tools

AWS SageMaker

Job description

Amazon seeks a Machine Learning Solutions Architect to lead model customization and inference across the AMERICAS, enabling foundation models, custom training, and scalable deployment on AWS.

You will design end-to-end ML architectures spanning data prep, distributed training, fine-tuning, and inference optimization, working with SageMaker AI and HyperPod to deliver scalable, cost-efficient solutions for diverse customers.