Senior MLOps Engineer: Production, FinOps & Observability

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

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.