Forward Deployed Engineer - MLOps

Systems Limited; Lahore; On-site; PKR 3,000,000 - 5,400,000; Full time

Job summary

Systems Limited is seeking an experienced MLOps leader to own the production lifecycle of ML models, ensuring reliable deployment, monitoring, and maintenance at scale. The role focuses on MLOps, cloud infrastructure, automation, observability, and production incident management.

You will collaborate with Data Scientists and ML Engineers to design scalable, production-ready systems, build retraining/versioning pipelines, and optimize cloud costs through FinOps.

Qualifications

• 6+ years in MLOps or ML Platform Engineering with production ownership.

Responsibilities

• Own production serving, CI/CD, deployment, and monitoring of ML models.
• Build and maintain retraining, versioning, and deployment pipelines.
• Manage ML infrastructure and optimize cloud costs via FinOps practices.
• Implement observability, alerting, drift detection, and performance monitoring.
• Own production incident response and on-call duties.
• Collaborate with Data Scientists and ML Engineers to design scalable, production-ready systems.
• Support presales and PoCs by demonstrating production readiness and scalability.
• Mentor engineers on MLOps and production-readiness best practices.
• Communicate infrastructure cost, performance, and reliability trade-offs to non-technical stakeholders.

Skills

CI/CD

Containerization

Cloud infrastructure

ML observability

Model lifecycle

Infrastructure as Code

Automation pipelines

FinOps

Monitoring

On-call incident response

Tools

Terraform

Docker

Kubernetes

AWS

Azure

GCP

Job description

Own the production lifecycle of machine learning models, ensuring validated models are reliably deployed, monitored, optimized, and maintained at scale. The role focuses on MLOps, cloud infrastructure, automation, observability, cost optimization, and production incident management.

Responsibilities:

• Own production serving, CI/CD, deployment, and monitoring of ML models.
• Build and maintain model retraining, versioning, and deployment pipelines.
• Manage ML infrastructure and optimize cloud costs through FinOps practices.
• Implement observability, alerting, model drift detection, and performance monitoring.
• Own production incident response, troubleshooting, and on-call responsibilities.
• Collaborate with Data Scientists and ML Engineers to design scalable, production-ready systems.
• Support presales and PoCs by demonstrating production readiness and scalability.
• Mentor engineers on MLOps and production-readiness best practices.
• Communicate infrastructure cost, performance, and reliability trade-offs to non-technical stakeholders.

Qualifications:

• 6+ years of experience in MLOps, ML Platform Engineering, or related roles with proven production ownership.
• Strong expertise in CI/CD, containerization, cloud infrastructure, and ML observability.
• Deep understanding of the ML model lifecycle, including retraining, model versioning, and drift detection.
• Experience with Infrastructure as Code (IaC) and automated deployment pipelines.
• Strong knowledge of major cloud platforms such as AWS, Azure, or GCP.
• Experience with cloud cost monitoring, optimization, and FinOps practices.
• Strong understanding of monitoring, alerting, SLA management, and production incident response.
• Ability to troubleshoot and communicate technical incidents clearly to business stakeholders.
• Strong collaboration and mentoring skills.
• Willingness to participate in on-call and off-hours production support.