
Instacart · Remote
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...
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 Search & Personalization ML team is Instacart’s engine for state-of-the-art multi-task, multi-objective ranking—unifying
search, discovery, recommendation, ads, and merchandising into a single value-aware platform. Partnering with world-class
engineers, scientists, and PMs, we build the ranking backbone that powers every pixel of the shopping journey, optimizing not just
for clicks, but for incremental GTV, basket lift, and retention over the long run.
What We’re Building
relevance, conversion, margin contribution, churn risk, and ad quality, enabling consistent decisions across search and
recommendations.
calibrated constraints on quality, diversity, fairness, and spend pacing—plus guardrails for safe exploration.
cold-starts, and feed the ranker with reasoning-rich context, while remaining the source of truth for final ordering.
Our commitment to AI innovation is reflected in our recent publications and research contributions to the field.
About the Job
merchandising into a single adaptive platform.
move beyond short-term engagement.
propensity, margin, and churn risk—ensuring calibration, constraints, and explainability.
latency optimization.
pipelines for tracking incremental GTV and retention.
About You
Minimum Qualifications
recommendation systems in production.
experience; experience with online testing and attribution beyond CTR.
frameworks (TensorFlow/PyTorch).
Preferred Qualifications
uplift/causal modeling, and/or contextual bandits for exploration.
and A/B testing infrastructure, with expertise in constraint-aware inference.
the ranker should arbitrate.
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.
WA
All other states
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 As a Senior Machine Learning Engineer II on the Ads Response Prediction team, you will lead the design and development of core ML models that power Instacart’s ads ecosystem. This is a research-leaning role focused on theoretical problem formulation, training methodology, and model quality rather than infrastructure or full-stack engineering. You will tackle fundamental challenges in pCTR modeling such as mitigating selection bias, position bias, and optimizer’s curse in training data, improving model calibration across surfaces and domains, and advancing our multi-task learning and sequence modeling capabilities. You will also have the opportunity to shape our next-generation foundation model approach for ads ranking and contribute to cutting-edge retrieval systems like TIGER (Transformer Index for Generative Recommenders), Semantic ID and domain language models. The Ads Response Prediction team owns all systems, algorithms and ML models to ensure a relevant and engaging Ads experience to customers of all the platforms powered by Instacart. This includes search and exploration retrieval systems, sequential modeling and generative retrieval systems for next interaction recommendations, LLM integrations, relevance models, pCTR models, bidding models and incrementality models. The team optimizes for an efficient marketplace to ensure delightful customer shopping experience, desirable advertiser business outcome and Instacart Ads revenue. The team has strong ML infrastructure and MLOps support, including Delta/DBT-Spark data pipelines, Ray-based distributed training, and automated model deployment. This means you can focus your energy on advancing modeling science rather than building infrastructure. ABOUT THE JOB * Lead research and development of pCTR and conversion prediction models, with a focus on improving calibration, reducing training data biases (selection bias, position bias, optimizer’s curse), and advancing model accuracy across Instacart’s ads surfaces. * Design and implement debiasing techniques such as Mixed Negative Sampling (MNS), Inverse Propensity Weighting (IPW), counterfactual risk minimization, and calibration methods (Platt scaling, isotonic regression) to address systematic prediction biases. * Contribute to the next-generation Multi-Domain Multi-Task (MDMT) model architecture, incorporating innovations like Mixture-of-Experts (MoE), Transformer layers for sequential user behavior, and LoRA adaptors for scalable domain fine-tuning. * Drive sequence modeling initiatives including the TIGER generative retrieval system and Semantic ID representation learning, expanding their application across ads surfaces such as Product Details, Search and other placements. * Collaborate with the broader ML community in the company on the path toward Foundation Models using autoregressive user behavior prediction. * Formulate and scope ambiguous modeling problems from first principles. Translate business observations (e.g., overcalibration patterns, cold-start underperformance) into well-defined ML research directions with clear evaluation criteria. * Publish and present findings internally. Contribute to the team’s culture of technical rigor through design reviews, paper sharing, and experiment retrospectives. ABOUT YOU MINIMUM QUALIFICATIONS * PhD/Master in machine learning, statistics, computer science, information retrieval, or a closely related quantitative field. * 6+ years of combined academic and industry experience (including PhD research) applying ML to ranking, recommendation, or prediction problems at scale. * Deep understanding of CTR/conversion prediction modeling, including familiarity with architectures such as Deep & Wide, DeepFM, DCN, and multi-task learning formulations. * Strong foundation in causal inference, counterfactual reasoning, and training data bias mitigation. Ability to reason about selection bias, position bias, and propensity-based correction methods. * Proficiency in Python and deep learning frameworks (PyTorch, Tensorflow, JAX). Fluency in data manipulation tools (SQL, Spark, Pandas). * Track record of formulating ambiguous problems into well-scoped ML research directions and delivering results through rigorous experimentation. * Strong written and verbal communication skills. Ability to explain complex modeling decisions to cross-functional stakeholders including product managers and data scientists. PREFERRED QUALIFICATIONS * Experience in ads ranking or auction-based systems (pCTR, bid optimization, ROAS feedback loops, marketplace dynamics). * Hands-on experience with autoregressive sequence models for user behavior prediction, generative retrieval, or transformer-based ranking architectures. * Familiarity with learned representations such as Semantic IDs, product embeddings, or other approaches to reducing feature cardinality and cold-start challenges. * Experience with transfer learning or domain adaptation techniques (e.g., LoRA, adapter-based fine-tuning) applied to recommendation or ranking models. * Publication record in top-tier venues (KDD, WWW, RecSys, NeurIPS, ICML, SIGIR, or similar). * Experience mentoring junior engineers or shaping technical direction for a modeling team. * Familiarity with LLM-driven approaches to recommendation, including prompt-based personalization and AI-assisted model development (AutoML). #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 $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
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here. Pinterest helps Pinners discover and do what they love. Core Engineering touches every surface the Pinner sees across the app and forms the front-and-center of the Pinterest experience for 500M+ Pinners every month. The Core team’s mission is to recommend inspiring & engaging pins for all our Pinners. We are looking for a Machine Learning Engineer Engineering Manager II who can drive the team’s technical direction, strategic planning and execution. You'll have the opportunity to lead a team that works cross-team on various innovative projects of new product experiences, builds large-scale low-latency systems and state-of-the-art machine learning models, and delivers great impact to our pinners and business metrics. What you’ll do: * Be responsible for major areas of search, recommendations, notifications, etc for more than 500 million monthly active Pinterest users. Potential areas of impact include ML based retrieval, multi domain ranking, L1 modeling, candidate generators, sequence modeling, relevance modeling, and infrastructure efficiency and scalability * Deeply understand the Pinterest product and drive the vision for the team, ensuring the team’s work directly contributes to the company’s goals * Manage and mentor a team of Machine Learning engineers (L13 - L16), providing technical guidance and support to help them grow their careers. Identify team needs and hire strong candidates * Collaborate closely with other engineering teams at Pinterest to enhance the experience for users, including Advanced Technology Group, Infrastructure, Content Understanding and User Understanding * Provide visibility to senior leadership regarding the team’s global impact * Partner with stakeholders across the company, including product management, data scientists, and design, to shape the future of the content ecosystem and personalization at Pinterest * Build a culture of excellence and expertise within the team What we’re looking for: * MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences, related field, or equivalent experience * Experience leading and working on a large-scale production recommendation, e-commerce, search or ads systems that are based on state-of-the-art machine learning and big data technology * Strong experience in related fields such as recommendation systems and applied machine learning experience is required. Natural language processing and computer vision is a bonus * Demonstrated ability to define and drive the strategic roadmap for scalable, production-quality systems from concept to execution * Strong focus on product impact and user experience within a consumer-focused environment * Minimum of 1 year of experience managing a high-performing machine learning engineering team of 10+ members * 8+ years of experience in software development, with a proven track record of delivering impactful solutions * Nice to have: * Experience with Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring * Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration Relocation Statement: * This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. In-Office Requirement Statement: * We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection. * This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country. #LI-REMOTE #LI-DM57 At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise. Information regarding the culture at Pinterest and benefits available for this position can be found here. US based applicants only $189,308—$389,753 USD Our Commitment to Inclusion: Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support. By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire.
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here. The Conversion Visibility Modeling team enables a performant ads marketplace and helps prove value to advertisers by connecting Pinterest onsite activity with conversions that happen offsite (both digital and physical) in a privacy-preserving way. As a Machine Learning Engineering Manager on this team, you will lead a hybrid team of ML engineers and backend software engineers to build end-to-end identity and conversion visibility solutions across modeling, serving, and data infrastructure, so advertisers retain accurate, privacy-aware performance visibility as signals fragment and degrade. You will set the technical direction for high-impact ML systems that feed ranking, bidding, measurement, and reporting across Pinterest’s ads stack. What you’ll do: * Attract, hire, develop, and lead a hybrid team of ML engineers and backend software engineers, fostering strong collaboration across modeling and infrastructure and building an inclusive, high-performing environment where the team can deliver end-to-end solutions. * Lead a team responsible for the strategy, execution, and operational excellence of identity and conversion signal modeling systems (e.g., user match prediction, conversion type/value prediction, probabilistic attribution and deduplication) that improve match precision/recall and downstream conversion quality across web and app surfaces. * Partner closely with product managers, data scientists, and tech leads to shape problem definitions, translate business needs into technical strategy, and drive execution toward high-impact outcomes. * Collaborate closely with Ads Ranking & Bidding, Measurement Products, and Conversion Ingestion & Attribution teams to define interfaces, SLAs, and success metrics that enable end-to-end identity and conversion visibility systems—including models, data pipelines, and serving surfaces—to integrate cleanly into the broader ads ecosystem. * Establish engineering best practices across both ML and backend development, including data quality, feature and data pipelines, model evaluation, experimentation, service reliability, and operational excellence, so the team can build trustworthy ML-powered systems end to end. * Use AI to accelerate analysis and iteration on model ideas and architectures, while applying strong judgment, testing, and verification to ensure correctness, reliability, and advertiser trust. What we’re looking for: * 7+ years of experience building and deploying large-scale ML systems in production (e.g., ads, measurement, recommendation, ranking, or search). * 2+ years of experience as an engineering manager or technical lead. * Bachelors Degree in Computer Science, Statistics, or a related technical field, or equivalent experience. * Nice to have: Meaningful hands-on experience or strong familiarity with ads conversion attribution, identity matching, ads ranking or ads measurement domains. * Proven technical leadership across both ML and software systems, with experience setting direction for multi-quarter roadmaps that span modeling, data pipelines, backend services, and productionization, and aligning stakeholders on priorities, trade-offs, and execution plans. * Excellent cross-functional communication and collaboration skills, building strong partnerships with product, data science, infra, and partner ML teams to clarify ambiguous problem spaces, co-create solutions, and drive consensus with senior stakeholders. Relocation Statement: * This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. In-Office Requirement Statement: * We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role. * This role will need to be in the office for in-person collaboration 1 day per week and therefore needs to be in a commutable distance from one of the following offices [Seattle or Bay Area]. #LI-AK7 #LI-HYBRID At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise. Information regarding the culture at Pinterest and benefits available for this position can be found here. US based applicants only $189,308—$389,753 USD Our Commitment to Inclusion: Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support. By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire.