About the Role

GOJEK Data Science works on some of the most interesting problems in transport, logistics and economics. We leverage machine learning to build data products for ride-hailing, logistics, food delivery and payments. From selecting the right driver to dispatch, to dynamically setting prices, to serving food recommendations, to forecasting real-world events, hundreds of millions of orders per month, across more than 18 products, are all driven by machine learning.

As a software engineer on the data science platform team you will be tasked with designing and building our machine learning infrastructure and platform. This requires a deep understanding of the machine learning life cycle and how data scientists turn hypotheses into production systems. You will be tasked with designing and building the products that data scientists leverage at each stage of the machine learning life cycle, ensuring a rapid time to market for ML projects.

Responsibilities

• Work closely with data scientists and machine learning engineers to understand their workflow and infrastructure needs
• Build robust infrastructure to operationalize and deploy machine learning systems
• Improve data scientists’ time to market for machine learning projects
• Scale the number of projects, users, and systems that our machine learning platform can support
• Ensure high throughput and availability of our machine learning frameworks

Experience and Skills

• 5+ years experience as a software engineer
• Experience with object-oriented programming
• Expertise in one of Go, Python or Java
• Experience operation production systems at scale: large data volume, high throughput and low latency
• Experience with distributed systems
• Experience working with both relational and non-relational databases
• Ability to write thorough, scalable and clear design documentation
• Understanding of cloud infrastructure (GCP/AWS)
• Experience deploying, maintaining and orchestrating microservices: networking, Kubernetes
• Keen eye for automation and building low-maintenance systems
• Experience with DevOps/SRE best practices
• Proven track-record building
• Ability to thrive within a fast-paced startup environment