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    Staff, Backend Engineer - Seoul, 대한민국. - Coupang

    Coupang
    Coupang Seoul, 대한민국.

    1주 전

    Coupang background
    설명

    Staff Backend Engineer – Data Science Engineering

    [Description]

    We exist to wow our customers. We know we're doing the right thing when we hear our customers say, "How did we ever live without Coupang?" Born out of an obsession to make shopping, eating, and living easier than ever, we're collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.

    We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurial surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.

    Our mission to build the future of commerce is real. We push the boundaries of what's possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

    [Job Overview]

    The global operations data science engineering organization (GODSE) within Fulfillment and Transportation Systems (FTS) Technology is responsible for building efficient and scalable online decision-making and offline decision support systems to solve business problems. These systems include logistics network design, warehouse order picking, warehouse layout (stow recommendation, SKU slotting), first-, middle-, and last-mile delivery, revenue management (route pricing), and labor management systems, to name a few. These systems are integral parts of efficient warehouse and logistics operations, which allow Coupang to offer even faster fulfillment times with more coverage and at lower costs. They are key to the bottom line of Coupang Corp.

    These systems are extensively integrated with warehouse management and logistics systems, covering everything from order processing to warehouse operations and logistics delivery. The desired candidate will help GODSE build systems that drive the overall process and workflow of Coupang's warehouse and logistics systems. This work will not only include designing and building world-class systems but also driving the adoption of advanced technologies in automation, robotics, and process optimization.

    [Key Responsibilities]

    Lead and drive architecture design of GODSE systems for scale, extensibility, and reliability

    Envision and drive alignment with stakeholders of the appropriate roadmap and direction of technology for GODSE

    Navigate and alleviate technical obstacles and blockers at the organizational level

    Decompose complex problems into simple, straightforward solutions, providing mechanisms for the teams to prioritize ruthlessly and "move with urgency."

    Write code when necessary to lead by example and help with high priority projects

    Proactively identify opportunities in both business and technology

    Review, advise, and carry out the adoption of new technology (both open-source and commercial) that are useful in achieving business objectives

    Lead the architecture design and implementation of services and systems using ML/OR models for business optimization through collaboration with data scientist, product owner, and domain team software engineers

    Design and implement an Online / semi-online serving system of ML/OR model through Backend Server

    Collaborate with the business domain team to integrate into the domain team's services.

    Build a system that can track the input/output of the model used in the service, and design, implement, and operate a system that can simulate / replay / debugging the model

    Provides ways to increase the productivity of data scientists' analysis work and creates a better environment.

    Consider ways to improve productivity when creating production services of the ML/OR model, and propose and implement a service / framework / platform

    Collaborate with the ML platform team to provide use-cases for services needed by the team and find efficient ways to implement model serving and data serving by utilizing the ML Platform team's services.

    [Basic Qualification]

    7+ years of experience in software development at technology companies

    7+ years of experience in developing and operating backend services and web applications

    Experience with Java and Python languages and proficient in using at least one of the two languages

    Solid track record of delivering large and complex systems with significant business impact

    Experience of designing and developing large-scale distributed systems and architectures

    Broad and deep understanding of key technologies in storage, data processing, and serving

    Excellent communications and collaborations across teams and across functionalities

    Capable of object-oriented design and development

    Service development and operational experience in an AWS environment

    Experience driving improvements in code quality

    Experience in automating build/test/deploy

    Experience with Git system for version control

    Experience with relational and column-oriented databases

    Agile experience

    [Preferred Qualifications]

    Python backend experience and proficient use of the Python language

    Proficient in using Spark / Airflow

    Practical experience related to data science and machine learning

    Love to learn and apply new technologies

    Experience with logistics-related / warehouse-related service development

    Experience in design and implement a semi-online / offline model serving system of ML/OR model through data pipeline.

    Experience in design and implement an ETL data pipeline for data required for model serving and a system that can serve the data.

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