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AI Infrastructure Engineer, AWS Trainium

🔥 0 minutes ago

🇺🇸 United States – Remote

đź’µ $76.7k - $150.8k / year

⏰ Full Time

🟡 Mid-level

đźź  Senior

đź‘· Infrastructure Engineer

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đź‘» Ghost score 2%

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Logo of Capgemini

Capgemini

10,000+ employees

Founded 1967

đź’Ľ Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Capgemini is a global leader in partnering with businesses to transform and manage their operations by harnessing the power of technology. With expertise across a wide array of industries such as aerospace, automotive, banking, and healthcare, Capgemini provides a constantly evolving portfolio of services to meet the ever-changing needs of their clients. Their offerings include cloud, cybersecurity, data and artificial intelligence, and enterprise management, among others. Capgemini also emphasizes innovation and sustainability, helping companies achieve digital transformation while promoting environmental and social responsibility. Additionally, Capgemini provides career opportunities across various levels and professions, encouraging innovation and diversity in its workforce.

đź“‹ Description

• Design, deploy, and manage scalable AI/ML infrastructure on AWS using Trainium, Inferentia, SageMaker, and EKS • Support distributed model training, inference, and deployment for Large Language Models (LLMs) and Generative AI applications • Optimize AI workload performance, resource utilization, and cost efficiency across cloud environments • Implement containerized and cloud-native solutions using Kubernetes, Docker, and Infrastructure-as-Code practices • Collaborate with AI engineers and data scientists to enable reliable, high-performance model development and deployment pipelines • Monitor, troubleshoot, and improve platform reliability, scalability, and operational excellence • Evaluate and implement emerging AI infrastructure technologies to support future business and technology initiatives

🎯 Requirements

• 5+ years in Cloud, Data, or AI Infrastructure • Experience supporting large-scale AI/ML training workloads in AWS environments • Exposure to Trainium or Inferentia is highly preferred • Experience with AWS Trainium, Inferentia, 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 Kubernetes (EKS), Docker, Python, PyTorch, and cloud-native architecture • Experience in AI performance optimization, benchmarking, and migration from GPU-based environments to AWS AI accelerators

🏖️ Benefits

• Vacation: 12-25 days, depending on grade • Company paid holidays • Personal Days • Sick Leave • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) • Life and disability insurance • Employee assistance programs • Other benefits as provided by local policy and eligibility • Additional compensation such as variable incentives, bonuses, or commissions may be available depending on the position and applicable laws

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