Machine Learning Ops Engineer

Roles & Responsibilities

A leader in Maritime space is currently expanding and looking for highly qualified candidates for the Machine Learning Ops Engineer position based in Singapore.

Job Responsibilities :

• Develop and maintain end-to-end ML pipelines for training, evaluation, and deployment
• Implement CI / CD workflows for ML models using cloud-native tools (e.g., Cloud Build, CodePipeline, Azure DevOps)
• Deploy and manage models on platforms like Vertex AI, SageMaker, or Azure ML, ensuring robust security and scalability
• Set up automated monitoring to detect model drift, performance issues, and data anomalies
• Maintain model registries and ensure proper versioning and lineage tracking
• Transition proof-of-concept models into production-grade system
• Build and optimize cloud ML infrastructure to accelerate deployment cycles
• Collaborate with cross-functional teams to ensure model reliability and performance in live environments

Requirements :

Airswift care deeply about equity, diversity and inclusion, and we actively seek talent from diverse and underrepresented groups. Please do send your CV to us if you meet most, but maybe not all of the requirements

Tell employers what skills you have

Excellent Communication Skills

Machine Learning

Scalability

Kubernetes

Azure

Pipelines

SageMaker

Software Engineering

Reliability

Python

Containerization

Vertex

Docker

Data Science

Scientific Computing

Orchestration