Description
About The Company Our client is an AI startup building intelligent supply chain solutions across Southeast Asia — from demand forecasting to inventory optimisation. They're a lean, engineering-first team that moves fast and gives engineers real ownership over the products they build. The Role They're looking for an ML Engineer to bridge the gap between data science and production — taking models built by their data science team and operationalising them into reliable, scalable systems.
This is a hands-on role sitting at the intersection of ML engineering and platform infrastructure. This is a greenfield opportunity — you'll be shaping how they build and operate ML systems from the ground up, with direct impact on a product used by major retailers across SEA. What You'll Do Own the deployment and operationalisation of ML models into production — building the infrastructure that takes models from development to live business systems Build and maintain ML platform tooling — experiment tracking, model versioning, model registry, and automated deployment pipelines using tools like MLflow and Airflow Implement model monitoring and drift detection to ensure production models stay accurate over time Build automated retraining pipelines so models stay relevant as data patterns change Work closely with data scientists to build self-serve tooling that enables them to deploy and iterate on models independently Deploy and manage ML workloads on cloud platforms (AWS, GCP, or Azure) using D
Full description, company and the link to apply — after you sign in.
Sign inEmployer contacts (email/phone/telegram) are hidden from the public preview —
send your CV, and we will connect you directly.