Machine Learning Engineer

Averis; Kuala Lumpur; Presencial; MYR 120.000 - 210.000; Jornada completa

Descripción de la vacante

Averis is hiring for an ML Pipeline Engineer to design and maintain production-grade ML pipelines for Computer Vision and GenAI applications. The role focuses on MLOps, automation, and scalable infrastructure across projects.

The ideal candidate has 3+ years in ML engineering, strong Python, and hands-on AWS (SageMaker, S3, ECR). Experience with Docker, CI/CD, and experiment tracking is essential for success in this role.

Formación

• 3+ years of experience in machine learning engineering and MLOps.
• Strong Python programming skills, with experience building maintainable and testable ML / data pipeline code.
• Hands-on experience with AWS services such as SageMaker, S3, ECR, or equivalent cloud ML infrastructure.
• Experience with Docker and CI/CD workflows for ML or data applications.
• Familiarity with experiment tracking, model versioning, and reproducible ML workflows.
• Good understanding of model training, evaluation and validation workflows.
• Strong communication and collaboration skills in cross-functional project environments.

Responsabilidades

• ML Pipeline Engineering: Build and maintain reproducible ML pipelines for Computer Vision and GenAI use cases.
• MLOps & Infrastructure: Build and maintain CI/CD workflows for ML code, including automated testing and containerization.
• Cross-project Engineering Support: Work across projects, contributing to shared ML engineering standards and reusable components.
• Labeling Support: Work with domain experts and annotators to deliver high quality labels for ML/CV projects.

Conocimientos

Python

AWS SageMaker

Docker

CI/CD

Experiment tracking

Model training

Data pipelines

Cross-functional collaboration

Herramientas

SageMaker

S3

ECR

Databricks

Descripción del empleo

Grow your career with us

Here at Averis, our common purpose is to improve lives by developing resources sustainably. Our people are crucial in helping us to realise our vision to be one of the best Global Business Solution (GBS) organization to support our customers in creating value for the Community, Country, Climate, Customer and Company.

Responsibilities:

This role is focused on ML engineering andMLOpsexecution , including pipeline development, model evaluation automation, and data / model lineage. It is not primarily a research or advanced modeling role.

Key Responsibilities

ML Pipeline Engineering

• Build and maintain reproducible ML pipelines forComputer Visionand GenAIuse cases
• Convert notebook-based or ad hoc workflows into version-controlled, testable, and maintainable pipeline components
• Standardize training, evaluation, and monitoring workflows across projects
• Improve data validation, artifact management, and handoff between data preparation, model inference, and downstream delivery

MLOps& Infrastructure

• Build and maintain CI/CD workflows for ML code, including automated testing and containerization
• Support ML development on AWS/Databricks, including services such as SageMaker, S3, ECR, andAI/MLExperiments
• Improve model reproducibility through standardized experiment tracking, configuration management, and lineage tracking

Cross-project Engineering Support

• Work across projects, contributing to shared ML engineering standards and reusable components
• Collaborate with data scientists, algorithm engineers, platform engineers, and business stakeholders to improve operational delivery
• Document engineering workflows, assumptions, and operational procedures to improve team scalability and maintainability

Labeling Support

• Work with domain experts and annotators to deliver high quality labels for ML/CV projects

Requirements

• 3+ years of experience in machine learning engineering andMLOps
• Strong Python programming skills, with experience building maintainable and testable ML / data pipeline code
• Hands-on experience with AWS services such as SageMaker, S3, ECR, or equivalent cloud ML infrastructure
• Experience with Docker and CI/CD workflows for ML or data applications
• Familiarity with experiment tracking, model versioning, and reproducible ML workflows
• Good understanding of model training, evaluation and validation workflows
• Strong communication and collaboration skills in cross-functional project environments

Preferred Domain Experience

Experience in one or more of the following is a plus:

• ComputerVisionML workflows
• GenAI workflows
• Experiment tracking and production ML monitoring

When you send us your resume and personal details, it is deemed you have provided your consent for us to keep or store your information in our database. All the information you have provided is only used for the recruitment process. Averis will only collect, use, process or disclose personal information where and when allowed to under applicable laws.
Only shortlisted candidates will be contacted for an interview. We endeavour to respond to every applicant. However, if you receive no response from us within 60 days, please consider your application for this specific position unsuccessful. We may contact you in the future if there are opportunities that match your qualifications and experience. Thank you for considering a career with Averis.