全职 Senior Machine Learning - Data Engineer 工作, 薪水, NielsenIQ WP Kuala Lumpur 公司招聘中 - Ricebowl

As a Senior Machine Learning Engineer, you’ll play a key role in turning innovative ML research into scalable, real-world solutions that power global decision-making. At NiQ, we’re looking for someone to join our Tech & Durable Global Data Science team, working at the intersection of data science and engineering to transform cutting-edge research into robust, production-ready systems. 

If you're excited by cloud technologies, MLOps, and solving complex problems with smart, data-driven approaches, and you thrive in a collaborative, learning-focused environment, this role is for you. 

What You’ll Do 

• Build & Scale ML Systems: Design, develop, test, deploy, and maintain machine learning solutions using software engineering best practices. 

• Productionize Prototypes: Transform data science models into scalable, production-ready systems for real-world applications. 

• Own the ML Lifecycle: Implement and manage end-to-end ML workflows using MLOps practices in both cloud and on-prem environments. 

• Collaborate Globally: Partner with data scientists, software engineers, and product experts in cross-functional, international teams. 

• Drive Engineering Excellence: Develop and refine tools, methods, and best practices to elevate ML engineering standards. 

• Mentor, Share & Grow: Support team development through mentoring, contribute to internal Communities of Practice, and engage in training and cross-functional learning opportunities. 

• Shape the Future of ML: Influence the direction of ML engineering at NIQ by contributing to strategic initiatives and technical roadmaps. 

Tech Stack You’ll Work With 

• Languages & Frameworks: Python, SQL, Argo, Kubeflow, MLflow 

• CI/CD Tools: GitLab CI 

• Monitoring: Prometheus, Grafana 

• Containers & Orchestration: Docker, Kubernetes 

• Databases: PostgreSQL, BigQuery, RDBMS 

Must-Haves 

• 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 

Nice-to-Haves 

• 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 is a plus.