Since its start in 2012, Instacart has expanded to 25 markets and partnered with 350+ retailers across the U.S. Our mission is to transform everyday life, and to achieve the goal, we innovate in a wide range of areas including e-commerce, advertising, and fulfillment. We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we build product and knowledge graphs on top of the catalog data to support a wide range of applications including search and ads.
We are looking for talented Ph.D. students to have an internship in our fast moving team. The students will have the opportunity to work on a very large scope of problems in search, ads, personalization, recommendation, fulfillment, product and knowledge graph, pricing, etc.
ABOUT THE JOB
Based on your passion and background, you may choose to work in a few different areas:
Query understanding - Using cutting-edge NLP technologies to understand the intent of user queries.
Search relevance and ranking - Improving search relevance by incorporating signals from various sources.
Ads quality, pCTR, etc. - Improving ads revenue and ROAS.
Knowledge graphs - Working on graph data management and knowledge discovery, and creating a natural language interface for data access.
Fraud detection and prevention - Using cost sensitive learning to reduce loss.
Pricing - Estimating willingness-to-pay, and optimizing revenue and user experience.
Logistics - Optimization in a variety of situations, including supply/demand prediction, last mile delivery, in-store optimization, etc.
Ph.D. student in computer science, mathematics, statistics, economics, or related areas.
Strong programming (Python, C++) and algorithmic skills.
Good communication skills. Curious, willing to learn, self-motivated, hands-on.
You can choose from a variety of local stores including Whole Foods, Safeway, Costco, Mariano's and many more, as well as being able to mix items from multiple stores into one order. Every day, we solve incredibly hard problems to create an experience for our customers that is nothing short of magical.