Machine Learning Engineer
HybridKuala Lumpur, Kuala Lumpur, Malaysia
Job Summary
Design, develop, test, deploy, and maintain machine learning solutions using software engineering best practices. Transform data science models into scalable, production-ready systems while implementing end-to-end ML workflows using MLOps practices in cloud and on-prem environments. Partner with data scientists, software engineers, and product experts in cross-functional, international teams to drive engineering excellence and influence the direction of ML engineering at NIQ. Mentor team members, contribute to internal Communities of Practice, and engage in training opportunities. Work asynchronously as part of a distributed team using Python, SQL, and containerization tools like Docker and Kubernetes to support global decision-making.
Required Qualifications
- Degree in computer science, engineering, statistics, or a related field (BSc, MSc, or PhD)
- 4+ years of experience in machine learning software development
- Strong Python skills and experience with ML libraries and frameworks
- Solid experience working in large-scale database environments
- Knowledge of containerization and orchestration (Docker, Kubernetes)
- Solid experience with production-level code quality and collaboration with software/testing engineers
- Solid understanding of statistical methods and machine learning algorithms
- Excellent stakeholder management and communication skills to align technical solutions with business needs
- Ability to work independently and asynchronously as part of a distributed team
- Professional working proficiency in English
Desired Qualifications
- Experience with cloud environments (AWS, GCP)
- Familiarity with MLflow or similar ML lifecycle tools
- Experience with agile development practices
- Background in forecasting, pricing, revenue assurance, or media analytics
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