MLOps Engineer – Commodities Conglomerate

We’re seeking an experienced MLOps Engineer to join the innovation team of a commodities conglomerate. In this role, you’ll be at the forefront of transforming upstream operations by developing scalable systems that can process vast amounts of data and deploy sophisticated machine learning models at scale. You’ll work closely with our data science team to bridge the gap between research and production, ensuring real-world impact in commodity market applications.

Role

You’ll design and implement robust ML pipelines on AWS and Databricks platforms, creating automated workflows that seamlessly ingest, process, and analyze continuous data feeds. Your expertise will be crucial in building scalable infrastructure capable of handling massive datasets while supporting real-time model inference for time-sensitive applications. You’ll also be responsible for optimizing cloud costs and large-scale data storage, ensuring operations remain efficient and cost-effective. Additionally, you’ll establish comprehensive model performance monitoring systems and implement automated retraining processes.

Requirements

We’re looking for a candidate with 4+ years of hands-on experience with AWS services including S3, EC2, SageMaker, and Lambda, along with proven expertise in the Databricks platform. You should be proficient in Python and Docker, with solid experience in machine learning frameworks such as TensorFlow and PyTorch. The ideal candidate will have experience with large-scale data processing and distributed computing environments. A Bachelor’s degree in Computer Science, Engineering, or a related field is required. Experience with MLflow, Kubeflow, or other AWS ML services would be a valuable addition to your profile.

Apply

To apply, please submit your resume to Yien Quek at yq@kerryconsulting.com. We regret to inform that only successful shortlisted candidates will be notified.

Licence No: 16S8060 | Registration no: R1109830