# DevOps Engineer (ML Infrastructure) Source: https://realanalystjobs.com/job/devops-engineer-ml-infrastructure-capgemini-5401db6a DevOps Engineer (ML Infrastructure) at Capgemini, an on-site role based in Toronto, Canada. Pay stated in the posting: $72,056- $138,940/year. First seen on RealAnalystJobs on 15 November 2026, read from Capgemini's own careers page (Capgemini), which RealAnalystJobs re-checks daily and removes the role when it closes. Updated 15 November 2026. ## Key facts - Company: [Capgemini](https://realanalystjobs.com/companies/capgemini) - Location: Toronto, Canada - Work mode: On-site - Pay stated in the posting: $72,056- $138,940/year - First seen: Nov 15, 2026 - Employment type: Full time - Source: Capgemini's careers page (Capgemini), re-checked daily Skills: [Python](https://realanalystjobs.com/skills/python), AWS, Azure ## Visa sponsorship The posting does not say. Capgemini had H-1B petitions approved for 2,110 workers in fiscal year 2026 (USCIS). That is history, not a promise for this role. [See the record](https://realanalystjobs.com/companies/capgemini#h1b-record) ## About this role At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same. Location This role is fully remote, anywhere in the Canada About the job you’re considering We are seeking a highly skilled Senior DevOps Engineer to help build, operate, and evolve large-scale, business-critical infrastructure platforms. This role focuses on reliability, scalability, automation, and operational excellence across distributed systems supporting high-volume production workloads. You will work closely with software engineers, platform teams, and infrastructure specialists to deliver highly available services, improve developer productivity, modernize infrastructure, and drive innovation through automation and AI-assisted operations. Your role • 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 utilization of GPU and compute resources. • Build and maintain CI/CD pipelines for ML services, infrastructure, and platform components. • Manage and optimize Kubernetes environments, including production workloads running 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 robust observability, monitoring, and alerting 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. Your skills and experience • Strong experience with Kubernetes and large-scale workload orchestration. • Hands-on experience with Kubernetes batch schedulers such as Volcano / 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 / Helm. • Experience designing and maintaining CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI/CD, or Azure DevOps and • Strong Linux systems administration and troubleshooting skills • Experience building observability solutions using: Prometheus, Grafana and • Understanding of ML lifecycle management, model deployment, and production operations. The base compensation range for this role in the posted location is: $72,056- $138,940/year Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: · Paid time off based on employee grade (A-F), defined by policy: 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 Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. Disclaimers Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, Description from Capgemini's public careers feed, reproduced so you can read the role here. Apply on the company's own site; Real Analyst Jobs never submits anything for you. ## How to apply Open [this role on Real Analyst Jobs](https://realanalystjobs.com/job/devops-engineer-ml-infrastructure-capgemini-5401db6a) and use Apply now there to reach the employer's application. The listing is re-checked against Capgemini's careers page daily and removed when it closes. ## Capgemini 222 open analyst roles on Real Analyst Jobs. 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