Staff ML Engineer (AWS Trainium & SageMaker)

Location: Remote - Canada

Company

AWS Partner building production AI systems and specialized engineering solutions for enterprise clients.

What you will do

• Train and operate machine learning models on Amazon SageMaker using AWS Trainium.
• Write and optimize PyTorch training code for Trainium, including NeuronCore architecture, compiler behavior, memory usage, and throughput.
• Diagnose data, code, compiler, and device-level issues in training runs.
• Build cost-aware, end-to-end SageMaker training pipelines from initial requirements through production deployment.
• Tune distributed training workloads for throughput and cost on SageMaker infrastructure.
• Work with client and internal engineering teams to scope and deliver production training workloads.

Requirements

• Strong hands-on experience with PyTorch, including distributed or multi-device training.
• Production experience with Amazon SageMaker for training and/or inference.
• Understanding of device-specific compilation and the ability to debug accelerator-related issues.
• Solid Python fundamentals.
• Experience working in a client-facing production engineering environment.

Nice to have

• AWS Trainium or Inferentia experience.
• Experience with the AWS Neuron SDK.
• Deep PyTorch experience and a proven ability to learn new hardware targets quickly.

Culture & Benefits

• Remote work in Canada.
• Forward-deployed work embedded directly with enterprise client teams.
• Focus on production systems rather than proof-of-concept experiments.
• Opportunity to work across the model, compiler, accelerator, and cloud infrastructure stack.