Staff Backend Engineer

Description

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.

The Global Operations Tech (GOT) organization is responsible for the systems that enable Coupang to reliably deliver to customers within hours of orders being placed. GOT is on a mission to innovate logistics by building an efficient delivery network at breakthrough scale and speeds. As a Staff Backend Engineer in GOT, you will leverage advanced algorithms to improve Coupang’s customer experience by ensuring ultra-fast deliveries are on time even during the busiest times of the year. We are looking for a Scientist that can drive the direction of technology across multiple teams, leverage deep industry knowledge and use statistical and machine learning techniques to bring value to customers. The ideal candidates are pragmatic, resourceful, and embrace challenges that are seemingly impossible. The ideal candidates also have rich industry experience and a track record of delivering highly impactful projects.

What You Will Do-

• Develop algorithms, simulation and systems at scale to improve warehouse, fulfillment centers, supply chain and\or transportation systems
• Expertise in Data Science, ML Ops and ML system design. Own and scale production-grade systems.
• Collaborate closely with the Operations and Product team to understand key business needs and formulate rigorous mathematical problems.
• Design features and build large-scale models and systems to improve network flow efficiency, for both inbound and outbound traffic.
• Effectively lead projects across teams and mentor team members.

Basic Qualifications

• Bachelors or Masters degree in a quantitative discipline: computer science, statistics, engineering, or equivalent.
• 7+ years of hands-on experience in building end-to-end systems and in ML Ops, including exploratory data analysis, feature engineering, sampling, model training with ensemble learning and/or deep learning, model validation, testing, serving, deployment and monitoring.
• Strong coding skills in Python or Java. Experience in data analysis with SQL, Numpy, Pandas. Proficient in toolings like Docker, Container, Kubernetes, AWS, Spark, Hive, Cassandra, Redis, Kafka, TensorFlow, Pytorch, Airflow, numpy, pandas, CI/CD.
• Excellent written and verbal communication skills while addressing both technical and business people; ability to speak at a level appropriate for the audience. The ideal candidate should be able to present business cases, and document models, analyses, and results to influence important decisions.
• Ability to deal with ambiguity in business and technology.
• Ability to work in a multicultural, cross functional team.

Preferred Qualifications

• 7+ years of hands-on experience in building and owning production-grade data systems, from ETL jobs to feature stores, to model training, deployment and monitoring.
• Experience in supply chains, transportation and logistics, and network optimization models.