Machine Learning PhD Intern, Economics (Fall)

Machine Learning Engineer, PhD Intern (Fall)

Instacart

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. 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. Machine learning is central to how we build intelligent shopping experiences at Instacart. We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. A few examples: * We build state-of-the-art models powering Search, Discovery, and Ads, combining generative AI and traditional machine learning to create best-in-class recommendations * We build rich product and knowledge graphs from catalog data imported from hundreds of retailers, applying them in recommendations and other user experiences * We redefine traditional domains across the company with AI, such as hyperpersonalized marketing and 0 → 1 meal planning products We are looking for talented Ph.D. students to join our fast-moving ML teams and work on high-impact problems at the intersection of LLM research, large-scale ML systems, and real-world e-commerce applications. ABOUT THE JOB Based on your passion and background, you may choose to work in a few different areas: * Query understanding: Using cutting-edge AI and LLM-based techniques to understand user intent, refine queries, and support downstream retrieval and ranking. * Search relevance and ranking: Improving search relevance by incorporating signals from user behavior, catalog knowledge, and generative models, including hybrid retrieval and ranking systems. * Generative recommendations: 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). * LLM evaluation and AIQA systems: Building LLM-based evaluation frameworks (e.g., LLM-as-a-Judge, self-critique) to improve the quality and reliability of generative and agentic systems. * Low-latency and scalable LLM systems: Researching techniques to deploy LLMs in high-traffic, latency-sensitive production environments, balancing quality, cost, and latency through cascading, distillation, and selective generation. * Knowledge graphs: 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. * Sequence modeling: Building temporal models for user behavior prediction. ABOUT YOU Minimum Qualifications: * 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 Preferred Qualifications:  * 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 Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here. Offers may vary based on many factors, such as candidate experience and skills required for the role. Please read more about our benefits offerings here.  For US based candidates, the base pay ranges for a successful candidate are listed below. 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 $44—$44 USD All other states $42—$42 USD

Senior Applied Scientist II, Ads Optimization

Instacart

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. OVERVIEW The Advertiser Optimization team is the decision-making engine of Instacart's $1B+ ads business. We own the systems responsible for Bidding, Pacing, Budgeting, and Targeting: converting stated advertiser goals into real-time auction actions. Our mission is to maximize realized Advertiser Value by deciding when to participate, how much to bid, and how fast to spend, all while balancing User Experience and Platform Revenue.   We are hiring a Senior Applied Scientist II to lead the algorithmic direction of these systems. This is a role for someone who thinks in terms of control theory, constrained optimization, and auction economics, and who can translate those frameworks into production code that makes millions of decisions per day. You will formulate problems from first principles, shape the technical roadmap, and own systems end-to-end from mathematical design through production deployment through impact measurement. ABOUT THE JOB * Design and evolve real-time bid optimization systems that translate advertiser goals (target ROAS, budget constraints) into optimal auction bids under uncertainty. Formulate the bidding problem as constrained optimization and build the feedback mechanisms that keep bids aligned with realized outcomes. * Build intelligent budget pacing algorithms that distribute spend across time and auction opportunities. The core challenge: allocating a finite daily budget across stochastic demand while maximizing total value, subject to advertiser constraints and time-varying conversion dynamics. * Develop the analytical frameworks that connect bidding, pacing, and budgeting into a coherent optimization objective. * Shape auction mechanics including reserve pricing, multi-slot allocation, and bid-to-price mapping. Reason about mechanism design tradeoffs between advertiser outcomes, platform revenue, and marketplace efficiency. * Own the full research-to-production loop: diagnose system behavior from large-scale data, formulate hypotheses, design experiments, ship production code, and measure impact. Write technical strategy documents that set the algorithmic direction for the team. ABOUT YOU MINIMUM QUALIFICATIONS * MS or PhD in operations research, applied mathematics, control systems, computational economics, or a related quantitative field. * 8+ years of experience building and deploying optimization or control systems in production environments (not just research prototypes). * Strong foundation in at least two of: feedback control theory (PID, MPC), convex and stochastic optimization, auction theory and mechanism design, dynamic programming. * Proficiency in one of the following languages: Go, Java, C++ for production systems and Python for data analysis and offline pipelines. * Demonstrated ability to translate mathematical formulations into production code that runs at scale (millions of decisions per day, sub-100ms latency constraints). PREFERRED QUALIFICATIONS * Experience with real-time bidding systems, ad auction optimization, or computational advertising at scale. * Background in budget-constrained allocation methods. Experience with adaptive control or model-predictive control in production systems. * Familiarity with causal inference and experimental design for evaluating algorithmic changes in marketplace settings. * Track record of shaping technical strategy and driving cross-functional alignment between engineering, product, and data science. Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here. Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here. For US based candidates, the base pay ranges for a successful candidate are listed below. CA, NY, CT, NJ $240,000—$253,500 USD WA $230,000—$243,000 USD OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI $221,000—$233,000 USD All other states $201,000—$212,000 USD

Senior Machine Learning Engineer, Operations Research

Instacart

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview: We are looking for a Senior Machine Learning Engineer with a strong Operations Research background to join the Service Availability & Routing team within Instacart's Logistics organization. In this role, you will work at the intersection of combinatorial optimization, mathematical programming, and AI to solve high-impact problems in the fulfillment space — including order batching, shopper routing, service availability prediction, and real-time assignment. You'll partner closely with engineering, product, and data science to ship models and algorithms that directly influence Instacart's profitability and shopper experience at scale. The Logistics & ML group is responsible for the intelligence and execution behind Instacart’s fulfillment system. The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high quality, shoppers get efficient and fulfilling work, and retailers and consumer brands get reasonable business. The team tackles hard problems in a variety of spaces, such as matching, pricing, and geospatial, as well as foundational problems executing on a high throughput system with dynamic data.   About the Job: * Design, develop, and deploy machine learning solutions to tackle practical challenges in the marketplace. * Collaborate closely with product managers, data scientists, and backend engineers to deeply understand business needs and create impactful ML applications. * Actively engage with diverse stakeholders to ensure that solutions are well-integrated and aligned with business goals. * Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models. About You: Minimum Qualifications: * Have a graduate degree (masters or PhD) in Operations Research or Industrial Engineering * 3+ years of industry experience using machine learning to solve real-world problems with large datasets * Have strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and Machine Learning (scikit-learn, XGBoost, Keras/Tensorflow) tools * Have strong analytical skills and problem-solving ability * Are a strong communicator who can collaborate with diverse stakeholders across all levels   Preferred Qualifications: * Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning and optimization techniques to solve marketplace problems #LI-Remote Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here. Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here. For US based candidates, the base pay ranges for a successful candidate are listed below. CA, NY, CT, NJ $207,000—$218,500 USD WA $198,000—$209,000 USD OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI $190,000—$205,000 USD All other states $173,000—$182,500 USD