Xcellink Pte

Enterprise ICT operations management provider

Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeSingaporeSGD5.5k - SGD7k

About the Job

Requirements

Skilled in Linux and Python, with knowledge of JavaScript or other scripting languages.
Experience with containerized applications, including Docker and Kubernetes, and ML infrastructure tools such as Kubeflow, MLflow, and RunAI.
Familiarity with end-to-end machine learning lifecycle management, including model development, training, validation, and deployment.
Ability to troubleshoot complex issues.
Preferably a minimum of 2 years of relevant work experience.

Responsibilities

Design, build, and maintain scalable machine learning infrastructure using tools such as Kubeflow, MLflow, and RunAI.
Automate the setup and management of machine learning environments and pipelines to ensure consistency and reliability.
Ensure automated testing and validation of AI and machine learning models before deployment.
Monitor model performance and health using logging, monitoring, and alerting tools.
Implement strategies for model retraining and updating based on performance metrics.
Collaborate with data scientists, engineers, and stakeholders to translate requirements into scalable machine learning solutions.
Participate in agile ceremonies, including sprint planning, daily stand-ups, retrospectives, and backlog grooming.

Machine Learning Engineer (AL-FNC250910 005/01)

Xcellink Pte Ltd · Singapore, Singapore · Contract · Posted 2025-09-10

Salary: SGD 5,500–7,000

Workplace: on_site

Department: Talent Placement

Description

We are looking for an ML Engineer to develop and scale our AI platform, build robust ML pipelines, and enable the deployment of AI workloads.

What You Will Be Working On

Design, build, and maintain scalable ML infrastructure using tools like Kubeflow, MLflow, and RunAI.
Automate the setup and management of ML environments and pipelines to ensure consistency and reliability.
Ensure automated testing and validation of AI/ML models before deployment.
Monitor model performance and health, using tools for logging, monitoring, and alerting.
Implement strategies for model retraining and updating based on performance metrics.
Collaborate with data scientists, engineers, and stakeholders to translate requirements into scalable ML solutions.
Participate actively in agile ceremonies such as sprint planning, daily stand-ups, retrospectives, and backlog grooming.

Requirements

Skilled in Linux and Python, with knowledge of JavaScript or other scripting languages.

Experience with containerized applications (Docker, Kubernetes) and ML infrastructure tools such as Kubeflow, MLflow, and RunAI.

Familiarity with end-to-end ML lifecycle management, including model development, training, validation, and deployment.

Strong problem-solving skills and ability to troubleshoot complex issues.

Excellent communication and collaboration skills.

Ability to work in a fast-paced, dynamic environment.

Continuous learning mindset to keep up with technological advancements.

Preferably minimum 2 years of relevant working experience.

Apply

Apply at Xcellink Pte Ltd

About the Company

Xcellink Pte

Enterprise ICT operations management provider

Xcellink Pte provides enterprise ICT operations management and enterprise solutions for global growth, local enterprises, and government-linked organizations. It delivers and runs IT services by managing data centre, network operations, security, helpdesk, onsite field services, applications support, and asset staging; it builds client operational teams from scratch and can offshore delivery to Malaysia, the Philippines, Indonesia, and India, scaling to hundreds of IT professionals. It differentiates itself through its long track record, ability to design end-to-end operations and offer analytics-driven enterprise solutions plus talent-search services for technology hiring. Its goal is to help clients achieve reliable IT delivery, optimize operations, and access skilled resources and innovative ideas as technology markets evolve.

Company size: 51-200
Company stage: Not listed
Total funding: Not listed
Headquarters: Singapore, Singapore
Founded: 1993

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