Machine Learning Engineer, PhD Intern

Instacart is transforming the grocery industry by making grocery delivery convenient, affordable, and accessible. They are seeking talented Ph.D. students to join their fast-moving machine learning teams to work on high-impact problems at the intersection of LLM research, large-scale ML systems, and real-world e-commerce applications.

Responsibilities:

• Using cutting-edge AI and LLM-based techniques to understand user intent, refine queries, and support downstream retrieval and ranking
• Improving search relevance by incorporating signals from user behavior, catalog knowledge, and generative models, including hybrid retrieval and ranking systems
• Pushing the boundaries of where generative and traditional models intersect across retrieval and ranking systems; developing scalable feedback and reward modeling approaches for closed-loop learning (RFT)
• Building LLM-based evaluation frameworks (e.g., LLM-as-a-Judge, self-critique) to improve the quality and reliability of generative and agentic systems
• Researching techniques to deploy LLMs in high-traffic, latency-sensitive production environments, balancing quality, cost, and latency through cascading, distillation, and selective generation
• Working on graph data management and knowledge discovery over one of the world’s largest grocery catalogs, and integrating structured knowledge with LLM-based reasoning and natural language interfaces
• Building temporal models for user behavior prediction

Requirements:

• Ph.D. student in computer science, mathematics, statistics, economics, or related areas
• Strong programming (Python, Golang) and algorithmic skills
• Solid foundations in machine learning, algorithms, or optimization
• Curious, self-motivated, and comfortable working on open-ended problems
• Ph.D. student at a top tier university in the United States
• Hands-on experience with generative or traditional modeling frameworks (PyTorch, Tensorflow, vLLM)
• Prior industry or research internship in machine learning or AI
• Interest and experience in translating research ideas into scalable production systems