Placement decisions to offer sharper promise to customers and increase sell through
Recommendation systems to provide optimal seller nudges for listing, replenishment etc.
Computer vision based ML models to automate manual audits thereby removing defects like incorrect listings, fake products etc. in a scalable way without human intervention.
Size and fit prediction for apparel and shoes
In this role you will:
Deeply involved in influencing the design of new product features by collaborating with product, engg. and design by having a point of view of how ML science can improve the product
Be a role model and provide guidance and mentorship to junior scientists on critical projects to resolve complex business problems.
Decompose complex problems into simple, straightforward solutions and provide mechanisms for the teams to prioritize ruthlessly and move with urgency.
Work with ML leadership to envision science roadmaps for the scalable and robust growth of Coupang's Rocket Growth's business.
Demonstrate science excellence by innovating with a variety of machine learning tools and science citizenship by percolating their use within the org
Dive deep into large amount of data sets from multiple systems to bring critical insights that can be transformed into business opportunities.
What we are looking for:
Master’s in Computer Science, Mathematics, Operation research, Machine Learning, AI, or equivalent quantitative fields.
10+ years’ experience in ML . Recent experience as a tech lead responsible for design of ML systems & models powering products at scale
Demonstrated joint problem identification and problem solving with Product and Engineering leaders to create science roadmaps for critical charters
Proficient in some of the ML training and deployment frameworks like: Tensorflow, PyTorch, TensorRT, Triton backend.
Ability to work in a fast-paced environment and to pivot as per business needs while ensuring focus on longer term architecture/use of right primitives etc.
Experience working in international environments with globally distributed teams.
