Machine Learning Ops Engineer

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:  

• Bachelor’s degree or higher in Computer Science, Software Engineering, or a related field      
• 3 years of hands-on experience in MLOps or ML infrastructure roles    
• Strong proficiency in Python and DevOps practices, including infrastructure-as-code (Terraform)   
• Experience with managed ML platforms (Vertex AI, SageMaker, Azure ML) 
• Skilled in containerization (Docker) and orchestration (Kubernetes)     
• Familiarity with CI/CD tools and monitoring stacks (e.g., Prometheus, Grafana, Cloud Monitoring)    
• Strong analytical mindset and problem-solving skills    
• Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders

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