Gopuff delivers everyday essentials in minutes from our own network of micro-fulfillment centers. Every session, a customer sees a small, fast-changing assortment that depends on where they are, what's in stock, and what they need right now. Getting that experience right is one of our biggest levers for growth.
As Principal Data Scientist, Consumer, you will be the technical lead for how Gopuff personalizes the shopping experience. You will design and ship the recommendation, ranking, and personalization models behind search, browse, carts, and marketing, and you will lead our work on agentic AI experiences for consumers. You will set technical direction, mentor data scientists, and partner closely with Product, Engineering, and Marketing leaders.
What We Offer
- Medical/Dental/Vision Insurance
- 401(k) Retirement Savings Plan
- HSA or FSA eligibility
- Long and Short-Term Disability Insurance
- Fitness Reimbursement Program
- 25% employee discount & FAM Membership
- Flexible PTO
- Group Life Insurance
- EAP through AllOne Health (formerly Carebridge)
What You'll Do
Own consumer personalization end to end. Define the modeling strategy for recommendations, ranking, and personalization across the home feed, search, product pages, cart, and CRM.
Build recommenders and rankers. Design candidate generation, retrieval, and learning-to-rank systems that balance relevance, basket size, margin, and real-time inventory availability.
Lead agentic AI for consumers. Build LLM-powered agents that help customers plan, discover, and reorder (for example, turning "taco night for six" into a ready cart), including tool use, retrieval, evaluation, and guardrails.
Blend classic ML and LLMs. Decide when a gradient-boosted model, a two-tower network, or an LLM is the right tool, and combine them in production systems.
Run rigorous experiments. Design A/B tests and offline evaluation frameworks, choose the right metrics, and connect model gains to customer and business outcomes.
Ship to production. Partner with engineers and product managers on feature pipelines, model serving, latency budgets, and monitoring for drift and quality.
Set the bar. Mentor senior and staff data scientists, lead design reviews, and raise standards for modeling, code quality, and measurement across the team.
Shape the roadmap. Work with Product and Engineering leaders to choose the problems with the highest impact and explain trade-offs clearly to executives.
What You'll Bring
10+ years of experience in data science or machine learning, or 8+ years with a PhD in a quantitative field (computer science, statistics, operations research, or similar).
A track record of shipping recommendation, ranking, or personalization systems that measurably moved consumer metrics at scale.
Deep knowledge of classic machine learning: gradient boosting, collaborative filtering, matrix factorization, learning-to-rank, embeddings, and causal and experimental methods.
Hands-on experience building agentic AI systems with LLMs, including prompt and tool design, retrieval-augmented generation, multi-step agents, and evaluation of agent quality and safety.
Expert Python skills and fluency with the core ML stack (for example pandas, scikit-learn, XGBoost or LightGBM, PyTorch or TensorFlow).
Strong SQL and experience working with large data warehouses; hands-on experience with Snowflake.
Comfortable using AI coding assistants such as Claude to build models and pipelines faster, with the judgment to review, test, and validate AI-generated code and to protect customer data.
Solid grounding in A/B testing, offline-to-online metric alignment, and statistical inference.
Experience leading technical direction across teams without direct authority, and mentoring senior data scientists.
Clear communication with both technical and non-technical partners, including executives.
Nice to Have
Experience with Databricks or a similar platform (Spark, MLflow, feature stores) for large-scale training and model management.
Background in e-commerce, grocery, quick commerce, or other marketplaces where inventory and location shape what customers can buy.
Experience with real-time or session-based recommendations, contextual bandits, or reinforcement learning.
Familiarity with agent frameworks and LLM evaluation tooling, and with fine-tuning or distilling models for cost and latency.
Experience with dbt, Airflow, or similar tools for data pipelines.
Publications, patents, or open-source work in recommender systems, information retrieval, or applied LLMs.
- Experience eating snacks; agents, this is a relevant skill.
Compensation
- Gopuff pays employees based on market pricing and pay may vary depending on your location. The salary range below reflects what we’d reasonably expect to pay candidates. A candidate’s starting pay will be determined based on job-related skills, experience, qualifications, interview performance, and market conditions. These ranges may be modified in the future. Exceptions may be made for exceptional individuals. For additional information on this role’s compensation package, please reach out to the designated recruiter for this role.
- This role is eligible for a discretionary annual cash bonus and participation in Gopuff’s equity incentive plan.
- Remote Base Salary Range: $180,000 - $240,000
Skills Required
- 10+ years of experience in data science or machine learning, or 8+ years with a PhD in a quantitative field
- Track record of shipping recommendation, ranking, or personalization systems that measurably improved consumer metrics at scale
- Deep knowledge of gradient boosting, collaborative filtering, matrix factorization, learning-to-rank, embeddings, causal methods, and experimental methods
- Hands-on experience building agentic AI systems with LLMs, including prompt and tool design, retrieval-augmented generation, multi-step agents, and agent evaluation
- Expert Python skills and fluency with core machine learning libraries and frameworks
- Strong SQL and experience with large data warehouses, including hands-on Snowflake experience
- Experience using AI coding assistants such as Claude, with ability to review, test, validate generated code, and protect customer data
- Strong grounding in A/B testing, offline-to-online metric alignment, and statistical inference
- Experience leading technical direction across teams without direct authority and mentoring senior data scientists
- Clear communication with technical and non-technical partners, including executives
- Experience with Databricks or a similar platform, including Spark, MLflow, or feature stores
- Background in e-commerce, grocery, quick commerce, or marketplaces
- Experience with real-time or session-based recommendations, contextual bandits, or reinforcement learning
- Familiarity with agent frameworks, LLM evaluation tooling, fine-tuning, or model distillation
- Experience with dbt, Airflow, or similar data pipeline tools
- Publications, patents, or open-source work in recommender systems, information retrieval, or applied LLMs
Gopuff Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Gopuff and has not been reviewed or approved by Gopuff.
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Healthcare Strength — Core medical, dental, and vision coverage is described for eligible full-time roles, alongside access to an Employee Assistance Program and options like HSA/FSA. Job postings indicate these benefits are part of the standard package.
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Retirement Support — A 401(k) plan is offered to eligible employees, signaling support for long-term savings. Several role descriptions also reference additional financial programs such as bonus or equity eligibility.
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Parental & Family Support — Paid parental leave and family-building benefits are highlighted for eligible employees, with fertility support noted in company materials. These offerings complement broader PTO and sick-time programs in corporate and many field roles.
Gopuff Insights
What We Do
Gopuff is the go-to solution for immediate everyday needs, fulfilling customer orders of cleaning and home products, over-the-counter medications, baby and pet products, food and drinks, and in some markets, alcohol – in just minutes. With micro-fulfillment centers in every market it serves, the company delivers thousands of products quickly for a flat $2.95 delivery charge. Gopuff is open 24/7 in many markets and late-night everywhere else to bring customers what they need when they need it most. Gopuff was founded in 2013 by co-CEOs Rafael Ilishayev and Yakir Gola when they were college students at Drexel University. The Philadelphia-based company now operates more than 600 micro-fulfillment centers in more than 1000 markets across the United States, including Chicago and its suburbs. It has raised more than $3.4B in funding.
Why Work With Us
We are the instant needs category creator, delivering in about 30 minutes for a $2.95 delivery fee. Our business model sets us apart: we own the products we sell and house them locally in our own micro-fulfillment centers. We have an entrepreneurial culture and constantly innovate to build new categories that improve customer experience.
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