Staff Machine Learning Engineer Full-time

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.