ML Platform Engineer — Real-Time Risk & Data Pipelines

Monee SG Private Limited; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Monee SG Private Limited in Singapore is seeking a Data / Machine Learning Engineer to build data and ML infrastructure for Credit Risk systems. You will collaborate with Data Scientists, Risk Policy, and Engineering to productionize models and maintain large-scale data pipelines.

The role focuses on real-time decision systems, model monitoring, data quality, and observability, with opportunities to improve developer productivity and AI-assisted platform improvements.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, Data Science, Artificial Intelligence, Machine Learning, Computer Engineering, Statistics, Applied Mathematics, or a related field.
• Minimum 3 years of experience in Data Engineering, Machine Learning Engineering, or a related field.
• Experience building data pipelines or ML systems in production.
• Strong programming skills in Python / Spark.
• Experience with large-scale data processing frameworks (Spark, Flink, etc.).
• Experience with workflow orchestration tools (Airflow or similar).
• Familiar with machine learning workflows and model deployment.
• Understanding of distributed systems and data infrastructure.
• Comfortable working with large-scale datasets and production systems.

Responsibilities

• Support deployment of ML models for real-time and batch risk decision systems.
• Build and maintain infrastructure for model serving and distributed inference.
• Assist in optimizing model performance, latency, and system reliability.
• Build and maintain data pipelines supporting model training and inference.
• Ensure feature consistency between offline and online environments.
• Develop and improve ETL / ELT workflows for large-scale data processing.
• Build monitoring systems for data quality, feature drift, and model performance.
• Investigate pipeline failures and troubleshoot production issues.
• Improve observability across data pipelines and model services.
• Explore AI to improve engineering workflows, such as pipeline diagnostics, data quality validation, model monitoring analysis, and developer productivity tools.
• Work closely with Data Scientists, Risk Policy, and Engineering teams.
• Support ML systems powering risk decisioning across multiple markets.

Skills

Python

Spark

Data pipelines

Large-scale data processing

Distributed systems

Airflow

Education

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

Tools

Spark

Flink

Airflow

Job description

Monee SG Private Limited in Singapore is seeking a Data / Machine Learning Engineer to build data and ML infrastructure for Credit Risk systems. You will collaborate with Data Scientists, Risk Policy, and Engineering to productionize models and maintain large-scale data pipelines.

The role focuses on real-time decision systems, model monitoring, data quality, and observability, with opportunities to improve developer productivity and AI-assisted platform improvements.