Jobs / Capgemini Engineering
AI Infrastructure Engineer
Capgemini Engineering · Toronto, ON, Canada
Toronto, ON, CanadaExp: 5+ yrs72,056-138,940 CADRemote
Remuneration
May include variable incentives, bonuses, or commissions, and benefits.
Location
Toronto, ON, Canada
Visa sponsorship
Not specified
Job summary
Design and operate scalable AWS infrastructure for large-scale AI/ML workloads, supporting distributed training, inference, and deployment for LLMs and Generative AI applications. Build and optimize cloud-native platforms using Trainium, Inferentia, SageMaker, EKS, Kubernetes, Docker, and infrastructure-as-code, while improving performance, cost efficiency, and reliability. Work with AI engineers and data scientists to enable high-performance model development and deployment pipelines.
Benefits
Paid time offVacationCompany-paid holidaysPersonal daysSick leaveMedical, dental, and vision coverageRetirement savings planLife and disability insuranceEmployee assistance program
Qualifications
- At least 5 years of experience in cloud, data, or AI infrastructure.
- Experience supporting large-scale AI/ML training workloads on AWS.
- Experience with AWS Trainium or Inferentia; exposure to either is preferred.
- Experience with EC2 Trn instances and AWS Neuron SDK for AI model training and inference.
- Strong understanding of LLMs, Generative AI, distributed training, and AI/ML infrastructure.
- Hands-on experience with EKS, Kubernetes, Docker, Python, PyTorch, and cloud-native architecture.
- Experience with AI performance optimization, benchmarking, and migration from GPU-based environments to AWS AI accelerators.
Responsibilities
- Design, deploy, and manage scalable AWS AI/ML infrastructure using Trainium, Inferentia, SageMaker, and EKS.
- Support distributed training, inference, and deployment for LLMs and Generative AI applications.
- Optimize workload performance, resource utilization, and cloud costs.
- Implement containerized cloud-native solutions using Kubernetes, Docker, and infrastructure as code.
- Collaborate with AI engineers and data scientists on reliable model development and deployment pipelines.
- Monitor, troubleshoot, and improve platform reliability and scalability.
- Evaluate and implement emerging AI infrastructure technologies.
Skills
AWSDockerEKSKubernetesPython
Industry
Engineering services
Relocation
No