Machine Learning Engineer, PhD Intern at Instacart

About The Internship

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, ads, personalization, recommendation, fulfillment, product and knowledge graph, pricing, and more.

Areas of Work

• 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. Candidate Qualifications

Minimum Qualifications

• 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.

Preferred Qualifications

• Ph.D. student at a top‑tier university in the United States.
• Prior internship/work experience in the machine learning space.

Past Internship Contributions Include

• Tensor‑based complementary recommendations, published at IEEE Big Data 2021 (Paper)
• Enhancing sequence‑based recommendations for long‑tail products (Blog)

Compensation and Benefits

The role is remote. Compensation varies by permanent work location.

• CA, NY, CT, NJ: $50—$50 USD
• WA: $47.50—$47.50 USD
• OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI: $45—$45 USD
• All other states: $42—$42 USD

Instacart provides highly market‑competitive compensation and benefits in each location where our employees work.