MLOps Engineer: Scale Production ML Platforms

FinTech Collective, LLC; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

Gen Kuala Lumpur is seeking an experienced MLOps Engineer to design, build, and operate the next generation of our ML platform, enabling data scientists and ML engineers to move models from experimentation to production at scale.

You will work closely with Data Scientists, Data Engineers, and AI/ML Engineering teams to streamline end-to-end workflows and improve system design for production-grade ML solutions.

Qualifications

• Bachelor’s degree in CS/SE/Data Eng or related field.
• Strong Python programming and production-grade services experience.
• Experience with cloud platforms (AWS, GCP, Azure) and Docker/Kubernetes.
• Experience building CI/CD pipelines for data or ML projects.
• Familiarity with ML frameworks and observability tools.
• Strong collaboration across Data Science, Data Engineering, Product and Operations.

Responsibilities

• Design, build, and operate ML infrastructure and tooling for full ML lifecycle.
• Develop and maintain CI/CD pipelines for ML models including testing and rollout strategies.
• Implement deployment patterns and ensure scalability and low latency in production.
• Build monitoring and observability for ML systems and define alerting processes.
• Collaborate with Data Scientists and ML Engineers to productize models and workflows.
• Integrate ML workloads into data platforms ensuring data quality and governance.
• Drive best practices in MLOps, including versioning, experiment tracking, and documentation.
• Contribute to security, compliance and cost optimization of ML infra.

Skills

Python

CI/CD pipelines

Cloud platforms

Docker

Kubernetes

Collaboration

Education

Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or related field

Tools

Docker

Kubernetes

GitHub Actions

GitLab CI

Jenkins

Terraform

Job description

Gen Kuala Lumpur is seeking an experienced MLOps Engineer to design, build, and operate the next generation of our ML platform, enabling data scientists and ML engineers to move models from experimentation to production at scale.

You will work closely with Data Scientists, Data Engineers, and AI/ML Engineering teams to streamline end-to-end workflows and improve system design for production-grade ML solutions.