Machine Learning - PhD Internship

OVERVIEW

Since 2012, Instacart has been focused on making grocery delivery convenient, affordable, and accessible to everyone. We bring fresh groceries and everyday essentials to customers across the US and Canada from nearly 55,000 stores across 5,500 markets. Our mission is to create a world where everyone has access to the food they love, and to achieve that 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. You will have the opportunity to work on a very large scope of problems in search, personalization, recommendation, 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.
• Knowledge graphs - Working on graph data management and knowledge discovery, and creating a natural language interface for data access.
• Pricing - Estimating willingness-to-pay, and optimizing revenue and user experience.

ABOUT YOU

Minimum qualifications:

• Currently enrolled in a Ph.D. in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Operations Research, or a related technical field.
• Experience in one area of computer science (e.g., Machine Learning, Deep Learning, Natural Language Understanding, Computer Vision, Algorithmic Foundations of Optimization, Software Engineering, or similar).
• Experience with one or more general-purpose programming languages, including Python, Ruby, Go, C/C++, Java, or similar.

• Experience in machine learning applications
• Experience in engineering projects and understanding of the engineering development cycle.
• Experience contributing to research communities or efforts, including publishing papers in major conferences or journals.