Fasten your helmet and climb on board if you're ready to be our next Machine Learning Engineer. In this role, you’ll be an instrumental player within the Data Science and Machine Learning team at GoPay - Southeast Asia's largest e-money wallet platforms and Indonesia's leading digital payments provider. You’ll focus your efforts on deploying and maintaining machine learning models for GoPay's products and services, refining and scaling these models, and crafting re-usable tools and frameworks for ML model deployment and monitoring. You’ll get ample opportunity to tackle and solve complex ML issues, and your efforts will help ensure a robust Gojek Payments platform.
What You Will Do
Work with data scientists to refine the ML model and scale it up
Create and maintain ML model training/prediction pipelines in production
Create re-usable tools and frameworks for ML model deployment and monitoring
Conduct internal workshops and external meetups, participate in external conferences, and give talks
What You Will Need
A Bachelor’s or Master’s in computer science, with at least 5 years of relevant work experience
Experience building production ML pipelines for model training/prediction
Experience working with large data sets, coming from varied sources
Experience working with open source ML libraries such as Tensorflow, PyTorch and XGBoost
Experience working with ML model training/deployment tools (such as Airflow, Kubeflow, Seldon)
Familiarity with data engineering tools (Flink/Spark/Kafka etc)
Experience with both object-oriented and functional programming concepts and languages
About the Team
Our GoPay Data Science team is a group of over 15 team members based across Singapore, India and Indonesia. Our role is to build critical ML components/models into the engineering systems to ensure GoPay remains a safe, trusted, and seamless way to conduct payments in Southeast Asia and beyond. Our team members come from varied backgrounds, and bring with them a wide set of skills and expertise (mathematics, statistics, machine learning, structured learning, among others) which we utilize to solve the complex business problems we're presented. We are enthusiastic about data science techniques and methods, as well as the business impacts of our models, and have numerous team forums where lively sharing discussions and presentations occur.
When we aren’t working, you’d probably find us whipping up new recipes in the kitchen, reading up on the latest best sellers, or trying to survive a brutal YouTube HIIT workout at home. We focus on nurturing and supporting one another both personally and professionally, and work together to get the job done.