Machine Learning Infrastructure, Software Engineer
Science – Machine Learning
This role is for you if you are comfortable with Big Data and Cloud infrastructure (we use Google Cloud), have a good familiarity with high-performance databases, and are keen on ensuring high reliability and efficiency in large-scale systems.
What You'll Do
- Design and build our Machine Learning Platform to help data scientists productionize their models and features faster
- Automate all parts of the data science lifecycle: feature engineering, model training, testing, and deployment
- Deploy, operate, and grow some of the largest ML systems in the region
- Collaborate with product teams to understand operational requirements. Translate these requirements into observable architecture and SRE processes
What You'll Need
- At least 3 years as an infrastructure or software engineer
- Experience with Go, Python, and shell script. Java optional
- Experience with cloud environments. Google Cloud preferred
- Experience with modern cloud deployment technology such as Terraform, Kubernetes, Helm
- Experience with operating and debugging Big Data frameworks such as Spark, Flink, Kafka, and Airflow
- Experience with relational and non-relational databases, preferably including clustering and high-availability configurations
- Experience with large-scale production systems and microservice architectures
- Familiarity with DevOps and Site Reliability Engineering (SRE) principles
The Data Science Platform (DSP) team is tasked with building out AI capabilities throughout Gojek. We are building out these capabilities through both our Machine Learning Platform and also by building solutions that bridge data science and product engineering.
Our work encompasses:
- Collaboration with data scientists and product teams in the development of innovative AI solutions
- Development of an end-to-end platform that enables ML practitioners to rapidly experiment and deliver AI solutions to production
- Production support for all systems deployed to the platform, thus freeing up data scientists from the operational burden while benefiting from economies of scale
- Use of our domain expertise to enable AI innovation throughout Gojek in the form of wide collaboration, education, and the introduction of best practices
This role 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.
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, serving food recommendations, forecasting real-world events, detecting fraud and preserving trust, we process hundreds of millions of orders per month, across more than 18 products, in four countries. All are driven by machine learning.
Gojek is a technology startup based in Jakarta, Indonesia. Specialising in ride-hailing and logistics, we are also the only company in Southeast Asia to be part of Fortune's 50 Companies That Changed the World (2017).
Gojek is a Super App: one app with over 20 services including food delivery, commuting, digital payments, shopping, hyper-local delivery, massages, and many more.
Gojek is Indonesia’s first and fastest growing unicorn building an on-demand empire. Our total of 2,000,000 driver-partners collectively travel 16.5 million KM daily – making us Indonesia’s de-facto transportation choice.
Gojek is a verb! Gojek is a way of life!