Machine Learning Engineer

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 and MLOps execution, 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 for Computer Vision and GenAI use 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, and AI/ML Experiments 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 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 Preferred Domain Experience Experience in one or more of the following is a plus: Computer Vision ML 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.