Machine Learning Engineer — Production ML & MLOps

Gen; Kuala Lumpur; Sur place; MYR 120 000 - 180 000; Plein temps

Résumé du poste

Gen is hiring a Machine Learning Engineer in Kuala Lumpur to build and maintain high-performing ML models in production. You will prototype, implement and experiment with methods to solve real business use cases, framing problems to drive value while collaborating with the Data Science and MLOps teams.

You will automate, architect and optimise ML processes, enforce test-driven development, and contribute to governance and tooling across the MoneyLion-like data stack.

Qualifications

• Strong mathematical, statistical or actuarial background.
• Proficient in Python and SQL.
• Hands-on experience in machine learning, predictive analytics and statistical modelling.
• Experience developing and deploying machine learning models in production.
• Adept at problem solving and troubleshooting from multiple perspectives.
• Strong communication and collaboration skills.

Responsabilités

• Frame and contextualize machine learning problems.
• Research, build and design ML systems and models to solve business problems.
• Assess data to select datasets for modelling and testing.
• Prototype and implement ML algorithms to improve products.
• Design, execute and monitor ML model experiments and metrics.
• Perform statistical analysis to prove business impact of improvements.
• Automate, architect and orchestrate ML processes and pipelines.
• Monitor, optimise and maintain ML solutions in production.
• Enrich ML libraries and governance tools to support model development lifecycles.
• Collaborate with MLOps Engineers and Data Scientists to improve system designs.

Connaissances

Python

SQL

Machine Learning

Statistical Modelling

Problem Solving

Outils

scikit-learn

XGBoost

LightGBM

Docker

Kubernetes

MLFlow

Description du poste

Gen is hiring a Machine Learning Engineer in Kuala Lumpur to build and maintain high-performing ML models in production. You will prototype, implement and experiment with methods to solve real business use cases, framing problems to drive value while collaborating with the Data Science and MLOps teams.

You will automate, architect and optimise ML processes, enforce test-driven development, and contribute to governance and tooling across the MoneyLion-like data stack.