AI DevOps Engineer (MLOps & Cloud)
At a glance
Mid-level ML Platform & Ops role at Dxctechnology. Petaling Jaya · full-time.
Pay not stated ML Platform & Ops salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and run secure cloud infrastructure that can scale for AI and machine-learning workloads
- Create infrastructure definitions and delivery pipelines for AI services and model releases
- Support models from training and version control through rollout and production monitoring
- Automate releases, configure system visibility, and tune compute, storage, and GPU use
- Resolve live system problems, guide developers and data scientists, and document infrastructure processes
What you bring
- At least five years in DevOps, site reliability, or platform engineering
- Hands-on experience putting MLOps workflows and AI or machine-learning systems into production
- Working knowledge of cloud platforms and infrastructure-as-code methods such as Terraform or CloudFormation
- Experience with containers, orchestration, and CI/CD tools, plus scripting in Python or Bash
- Fluent English and familiarity with security practices, observability, and secrets management
Who this fits
This role suits a mid-level engineer who can own reliable AI/ML infrastructure and work closely with AI engineers, data scientists, and infrastructure teams. It is based in Petaling Jaya, Malaysia, and the work model prioritizes in-person collaboration while allowing flexibility. Fluent English is required.
From the employer
Job Description:
DXC Technology (NYSE: DXC) is a leading enterprise technology and innovation partner delivering software, services, and solutions to global enterprises and public sector organizations — helping them harness AI to drive outcomes at a time of exponential change with speed. With deep expertise in Managed Infrastructure Services, Application Modernization, and Industry-Specific Software Solutions, DXC modernizes, secures, and operates some of the world's most complex technology estates. Learn more on dxc.com.
Key Responsibilities
Design, implement, and maintain scalable, secure cloud infrastructure for AI/ML solutions
Build and manage Infrastructure as Code (IaC) using tools such as Terraform or CloudFormation
Develop and maintain CI/CD pipelines for AI applications and model deployment
Support end-to-end MLOps lifecycle (training, versioning, deployment, monitoring)
Automate deployments using best practices (blue/green, canary releases, rollback strategies)
Configure monitoring, alerting, and observability (logs, metrics, tracing) for production systems
Optimize performance, scalability, and cost (compute, storage, GPU usage)
Use AI tools (e.g. Copilot, ChatGPT, Claude, Cursor) to accelerate scripting, automation, and incident resolution
Troubleshoot production issues and ensure high system reliability and availability
Support developers and data scientists on DevOps tooling and best practices
Implement DevSecOps standards, including security, secrets management, and compliance
Maintain clear technical documentation for infrastructure and processes
Skills & Experience
5+ years of experience in DevOps, SRE, or platform engineering
Strong experience in MLOps and deployment of AI/ML solutions in production
Proficiency with cloud platforms (AWS, Azure, or GCP) and related AI services
Expertise in Infrastructure as Code (Terraform, CloudFormation, ARM templates)
Hands-on experience with containerisation and orchestration (Docker, Kubernetes, Helm)
Strong CI/CD experience (GitHub Actions, GitLab CI, Jenkins, Azure DevOps)
Familiarity with MLOps tools (MLflow, Kubeflow, Weights & Biases, SageMaker Pipelines)
Proficiency in scripting and automation (Python, Bash)
Experience with monitoring and observability tools (Prometheus, Grafana, ELK, Datadog)
Knowledge of DevSecOps practices and security standards
Experience with secrets and configuration management (Vault, AWS Secrets Manager)
Preferred Skills & Attributes
Experience optimising AI workloads using GPUs
Ability to diagnose and resolve issues using AI-assisted tools
Strong problem-solving and analytical thinking
Pragmatic approach balancing automation, speed, and reliability
Attention to detail in infrastructure design and security
Proactive, with strong ownership and initiative
Strong collaboration and support mindset
Comfortable working in fast-paced, agile environments
Work Environment
Agile, fast-paced innovation environment
Close collaboration with AI engineers, data scientists, and infrastructure teams
Strong focus on automation, scalability, and production-ready AI systems
English-speaking environment (fluency required)
At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.
Recruitment fraud is a scheme in which fictitious job opportunities are offered to job seekers typically through online services, such as false websites, or through unsolicited emails claiming to be from the company. These emails may request recipients to provide personal information or to make payments as part of their illegitimate recruiting process. DXC does not make offers of employment via social media networks and DXC never asks for any money or payments from applicants at any point in the recruitment process, nor ask a job seeker to purchase IT or other equipment on our behalf. More information on employment scams is available here.