DevOps Engineer, ML Infrastructure

🕒 5 dias atrás

🇨🇦 Canadá – Remoto

💵 $72.056 - $138.940 / ano

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

⛑ DevOps & Engenheiro de Confiabilidade do Site (SRE)

👻 Score fantasma 2%

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🗣️🇺🇸🇬🇧 Inglês obrigatório

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Capgemini

10.000+ funcionários

Fundada em 1967

💼 Consultoria

🏥 Saúde

📦 Logística

Consulting • Healthcare • Logistics

A Capgemini é líder global em parceria com empresas para transformar e gerenciar suas operações aproveitando o poder da tecnologia. Com expertise em uma ampla gama de setores, como aeroespacial, automotivo, bancário e saúde, a Capgemini oferece um portfólio de serviços em constante evolução para atender às necessidades, em constante mudança, de seus clientes. Suas ofertas incluem Cloud, cibersegurança, dados e inteligência artificial (IA), e gestão empresarial, entre outras. A Capgemini também enfatiza inovação e sustentabilidade, ajudando as empresas a alcançar a transformação digital enquanto promove a responsabilidade ambiental e social. Além disso, a Capgemini oferece oportunidades de carreira em diversos níveis e profissões, incentivando a inovação e a diversidade em sua força de trabalho.

Descrição

• Build, operate, and evolve large-scale, business-critical infrastructure platforms • Develop and manage cloud-native infrastructure supporting large-scale ML workloads on Kubernetes • Implement and operate batch scheduling solutions such as Volcano and Kueue to optimize GPU and compute resource utilization • Build and maintain CI/CD pipelines for ML services, infrastructure, and platform components • Manage and optimize Kubernetes environments, including production workloads on AWS EKS and other cloud platforms • Lead and support infrastructure modernization and migration initiatives across cloud and platform ecosystems • Partner with Data Scientists, ML Engineers, and Software Engineers to productionize machine learning solutions • Implement observability, monitoring, and alerting for distributed systems and GPU clusters • Ensure platform reliability, security, scalability, and operational excellence • Troubleshoot complex distributed systems and performance bottlenecks across infrastructure and ML workloads • Improve developer productivity and drive innovation through automation and AI-assisted operations

🎯 Requisitos

• Strong experience with Kubernetes and large-scale workload orchestration • Hands-on experience with Kubernetes batch schedulers such as Volcano and Kueue • Solid understanding of distributed systems, containerization technologies, cloud-native architectures, and microservices-based platforms • Experience managing workloads on Kubernetes platforms such as AWS EKS • Proven track record delivering and supporting infrastructure migration projects • Strong programming skills in Python or Golang • Experience with Infrastructure-as-Code and deployment tools including Terraform and Helm • Experience designing and maintaining CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI/CD, or Azure DevOps • Strong Linux systems administration and troubleshooting skills • Experience building observability solutions using Prometheus and Grafana • Understanding of ML lifecycle management, model deployment, and production operations

🏖️ Benefícios

• Paid time off: Vacation (12–25 days depending on grade), company-paid holidays, personal days, and sick leave • Medical, dental, and vision coverage, or provincial healthcare coordination in Canada • Retirement savings plans, including RRSP in Canada • Life and disability insurance • Employee assistance programs • Other benefits provided by local policy and eligibility • Potential eligibility for variable incentives, bonuses, or commissions

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