Machine Learning - Ph.D. Internship
- Toronto, Canada
We're transforming the grocery industry
Instacart is the North American leader in online grocery and one of the fastest-growing companies in e-commerce. Since 2012, we've been working towards creating a world where everyone has access to the food they love and more time to enjoy it together.
Groceries delivered to your door in as little as an hour. It seems simple, right? Well, it's more complex than that. From re-routing deliveries during snowstorms, to connecting customers with coupons and deals for their favorite brands, to updating over half a billion grocery data lines every night...our efforts bring Instacart closer to being the operating system for the grocery industry.
Solving these problems is what helps our customers get back time in their day, so they can do more of what they love.
Introducing Our Hybrid Working Model
As the future of work evolves, so do we. We have a hybrid model where our roles are open to in-office, flex, or remote work. Learn more about our flexible approach to where we work.
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.
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