Focus areas:
- Economics driven inventory planning models
- 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.