NielsenIQ: Machine Learning Engineer — Kuala Lumpur, 14, Malaysia

About NielsenIQ

NielsenIQ, also known as NIQ, works in consumer intelligence and retail measurement. Its employer material describes using market information, consumer insights and analytics to help businesses understand buying behaviour. Its data operations address the accuracy and completeness of information behind client reports, while analytical services interpret that information. The business connects details about products and retail activity with broader views of markets, giving organisations evidence for understanding demand and making commercial decisions.

The position and its setting

NielsenIQ lists Machine Learning Engineer in Kuala Lumpur, 14, Malaysia, under reference R26_0005131|MY. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Employment type: Full-time
• Employer listing date: 22 October 2026
• Brands: NielsenIQ
• Job Family: Data Science and Business Intelligence Generalist/Multidiscipline

Responsibilities and work described

• 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
• Building: & 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
• Collaboration: 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

Essential requirements and candidate background

• 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
• Python skills and experience with ML libraries and frameworks
• Experience working in large-scale database environments
• Knowledge: containerization and orchestration (Docker, Kubernetes)
• Experience: production-level code quality and collaboration with software/testing engineers
• Understanding: statistical methods and machine learning algorithms
• Stakeholder management and communication skills to align technical solutions with business needs
• Work independently and asynchronously as part of a distributed team
• Professional working proficiency in English
• Nice-to-Haves
• Experience: cloud environments (AWS, GCP)
• Familiarity: MLflow or similar ML lifecycle tools
• Experience: agile development practices

Preferred experience and additional strengths

• Background in forecasting, pricing, revenue assurance, or media analytics is a plus

Location, schedule and contract conditions

For this overseas or regional listing, confirm work authorisation and any location restrictions with the employer. The location does not establish visa sponsorship or permission to work remotely from India.

• Work arrangement: On-site
• Advertised location: Kuala Lumpur, 14, Malaysia

Benefits mentioned by the employer

• 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
• 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

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Machine Learning Engineer vacancy is not an offer for reference R26_0005131|MY; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to NielsenIQ

Applications follow the official employer page linked below.

Open the official NielsenIQ posting below and match the title and reference R26_0005131|MY.

Compare your qualifications and experience with the essential conditions for the Kuala Lumpur, 14, Malaysia position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: Python

Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.

Relevant skills

• Python
• SQL
• Kubernetes
• CI/CD
• Docker
• AWS
• GCP
• AI/ML
• machine learning
• training
• Google Cloud