Machine Learning Engineer

Short Summary

Machine Learning Engineer with NielsenIQ. 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…

Key Details

• Position / opportunity: Machine Learning Engineer
• Organization: NielsenIQ
• Country / coverage: Malaysia
• Location: Kuala Lumpur, 14, Malaysia
• Work arrangement: On-site
• Opportunity type: Volunteer opportunities
• Sector: Education
• Compensation: Not specified
• Duration: Not specified
• Start date: 2026-08-13
• Application deadline: Not specified

Description

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. Benefits: • Exciting work environment that brings people together. • Use the latest digital technologies. • Ongoing trainings to support your development. • Opportunities for personal and professional growth. • Hybrid work Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://nielseniq.com/global/en/info/niqs-ai-safety-policies/ About NIQ NIQ is the world’s leading consumer intelligence company…

Responsibilities

• 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.

Requirements / Eligibility

• cation 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.

How To Apply

Use the Apply now button and follow the instructions on the application page.