Senior ML Engineer: Productionize & Scale ML Systems

NielsenIQ; Kuala Lumpur; Hybrid; MYR 180,000 - 280,000; Full time

Benefits offered by this job

Hybrid work

Flexible environment

Training & development

LinkedIn Learning

Job summary

NielsenIQ is seeking a Senior Machine Learning Engineer to turn cutting‑edge ML research into scalable, production‑grade solutions powering global decisions. You'll join the Tech & Durable Global Data Science team, collaborating across data science and engineering to transform research into robust systems.

If cloud, MLOps, and data‑driven problem solving excite you, and you thrive in a learning‑oriented, collaborative environment, this role is for you.

Qualifications

• Degree in computer science, engineering, statistics, or related field.
• 4+ years of experience in machine learning software development.
• Strong Python skills and ML libraries/frameworks.
• Experience with large-scale database environments.
• Knowledge of Docker and Kubernetes for production systems.
• Excellent communication and collaboration with cross-functional teams.

Responsibilities

• Design, develop, test, deploy, and maintain ML solutions.
• Productionize prototypes into scalable, production‑ready systems.
• Own end-to-end ML lifecycles using MLOps in cloud and on‑prem.
• Collaborate with global data scientists, engineers, and product teams.
• Develop tools and best practices to elevate ML engineering standards.
• Mentor teammates and contribute to internal learning communities.
• Influence ML engineering strategy and technical roadmaps.

Skills

English proficiency

Stakeholder management

Independent work

Distributed teams

Education

BSc/MSc/PhD in CS/Engineering/Statistics

Tools

Docker

Kubernetes

Kubeflow

MLflow

GitLab CI

Prometheus

Grafana

PostgreSQL

BigQuery

Job description

NielsenIQ is seeking a Senior Machine Learning Engineer to turn cutting‑edge ML research into scalable, production‑grade solutions powering global decisions. You'll join the Tech & Durable Global Data Science team, collaborating across data science and engineering to transform research into robust systems.

If cloud, MLOps, and data‑driven problem solving excite you, and you thrive in a learning‑oriented, collaborative environment, this role is for you.