If you’re looking to be a part of a dynamic, highly-analytical team who enjoys working on AI/ML solutions for a high-growth company, look no further. As a Principal Engineer, Machine Learning and Big Data for the Data Science Platform, you will be handed the reins in ensuring that the Data Scientists have all that they need in order to successfully bring magic into production. Working closely with Business heads, Data Scientists, and Engineering teams, you will help Gojek make thousands of model-powered decisions every second, on a daily basis. The cherry on top: you’ll get to work on a wide range of products across the Gojek ecosystem!
What Will You Do
- Collaborate with the Chief Data Officer, Chief Technology Officer, Head of Marketplace, and Data Science Platform product management to formulate ML product roadmap based on business needs
- Establish partnerships with various Data Science and Product Engineering teams across the entire Gojek group to understand their needs and to propose solutions integrating technologies from DSP, Google Cloud, or others, and incorporating ML Engineering best practices
- Lead in-depth technical discussions with the DSP team on the evolution of our various products and to work together with DSP PM to unify our products under the ML Platform vision
- Represent the needs of the DSP team, communicate our ML Engineering strategy and key DSP initiatives as a ML Platform, to the Gojek Senior Management, the Company and even external stakeholders
- As our most senior technologist, be actively involved in team development and growth, and defining the OKRs of the team and chart a path for the team’s growth
- Participate in recruitment and interviews to attract new talent, as well as mentorship and performance management of current team members
- Continue to stay abreast of the latest technologies in Machine Learning and Big Data space to inform the right choice between build vs buy, and to suggest new technologies and best practices to trial
What You Will Need
- Past experience in building and operating complex software systems, or experience with data platforms on a massive scale; preferably with product development experience
- Keen understanding of modern Agile, Site Reliability Engineering, and MLops practices
- Deep knowledge in one or more of these areas: Cloud, Big Data, and Machine Learning; we use Google Cloud, Kubernetes, and Spark extensively, while our primary languages are Golang and Python
- Some Data Science or Machine Learning qualifications or experience, to effectively collaborate with data scientists
- Experience managing business and engineering stakeholders, as well as roadmap or OKR planning within large organizations at a management level with business, product, and engineering
- Able to work in a fast-paced environment where business needs and organizational structures are rapidly evolving; Startup experience is much preferred, on top of experience in multinational, multicultural companies
- Ability to transition from high-level strategic thinking to creative and detailed execution
About the Team
Our Data Science Platform team, a subsidiary of the Marketplace Data team, consists of 15 Machine Learning and Infrastructure Engineers based in Singapore. Working alongside the Data Science teams, the team is unique in its charter as an enabler of Data Science and Machine Learning systems at production scale in a hyper-growth unicorn. You may know us as the creators of open-source MLops technologies such as Feast
, and Turing
, and internal tools such as Clockwork
. Our products are used in mission-critical parts of Gojek’s product offerings, such as dynamic pricing, driver allocation, food recommendations, and fraud prevention.
We are a tight-knit group made up of avid readers, amateur gamers, coffee connoisseurs and (guilty🙈) reality show watchers. We work hard and play hard, and believe it or not, we actually enjoy each other’s company!
Gojek is committed to building a diverse and inclusive workplace and is an equal opportunity employer. We do not discriminate on the basis of race, religion, national origin, gender, gender identity, sexual orientation, disability, age, education status, or any other legally protected status.