Engineering Manager (Big Data)

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About the Role
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 our Machine Learning and Big Data Principal Engineer for the Data Science Platform, you’ll take the wheel in managing a talented troop of data scientists, overseeing in their development and growth and defining OKRs to chart the team’s trajectory. As our most senior technologist, you’ll collaborate with senior-level stakeholders in formulating the ML product roadmap, and with various Data Science and Product Engineering teams to integrate technological solutions into their products, making model-powered decisions for a wide range of Gojek products on a daily basis.

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 and Google Cloud (among 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 with the DSP PM to unify our products under the ML Platform vision
Represent the needs of the DSP team, and communicate our ML Engineering strategy and key DSP initiatives as a ML Platform to the Gojek Senior Management, the Company, and external stakeholders
As our most senior technologist, be actively involved in team development and growth, defining the OKRs of the team and charting 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 on 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 try out

What You Will Need

Experience in building and operating complex software systems, or with data platforms on a massive scale, preferably with product development experience
Deep understanding of modern Agile, Site Reliability Engineering, and MLops practices
Deep knowledge in at least 1 of these fields: Cloud, Big Data, and Machine Learning; (we use Google Cloud, Kubernetes, and Spark extensively, while our primary languages are Golang and Python)
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 teams
Ability to work effectively in a fast-paced environment, where business needs and organizational structures are rapidly evolving; startup experience is much preferred, with experience in a multinational, multicultural company
Ability to transition from high-level strategic thinking to creative and detailed execution

About the TeamOur Data Science Platform team, a subsidiary of the Marketplace Data team, consists of 15 Machine Learning and Infrastructure Engineers based in Singapore. Our team is unique in its charter as an enabler of Data Science and Machine Learning systems at production scale within a hyper-growth deacorn. It’s our job to build and oversee a Machine Learning platform to accelerate ML product development and simplify operations here at Gojek.Some of our creations include open-source MLops technologies such as Feast (our feature store), Merlin (our model deployment platform), and Turing (our experimentation platform), 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 constantly work with machine learning practitioners to solve high-impact issues, and generalize the solution at a platform level to benefit the organization as a whole. We are a tight-knit group made up of exercise-buffs, amateur gamers, and (wannabe) whiskey connoisseurs. We work hard and play hard, and believe it or not, we actually enjoy each other’s company!

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