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Hungryroot Tech Stack

AI-driven grocery and recipe personalization with supply-chain optimization

Food and Beverage Services New York, New York 201–500 employees Founded 2015 Privately Held
hungryroot.com LinkedIn

Hungryroot pairs consumer-facing personalization (grocery recommendations, recipe generation, supplement suggestions) with heavy operational engineering: box-filling algorithms, inventory forecasting, and hybrid search infrastructure. The tech stack reveals a company balancing Python/Go backend work with modern ML (LangChain, scikit-learn, PyTorch) and operations research solvers (Gurobi, CPLEX, PuLP) — suggesting the core challenge is not discovery but logistics: how to optimize box fills and inventory given highly personalized demand. Current hiring is skewed toward senior engineers and data roles, signaling a push to scale algorithms and forecasting.

Tech Stack 25 technologies

Core StackLooker Google Analytics Heap Amplitude Figma Databricks NetSuite Cursor Sentry Datadog LangChain Python Go TypeScript scikit-learn PyTorch Swift SwiftUI LookML Dayforce Vercel AI SDK Gurobi CPLEX PuLP OpenSearch
AdoptingLangChain Vercel AI SDK

What Hungryroot Is Building

◆Challenges

  • Inventory forecasting
  • Supply chain optimization
  • Box filling optimization
  • Expanding recipe coverage
  • Improving content performance
  • Identifying workflow inefficiencies
  • Improving inventory tracking
  • Strengthening internal controls
  • Reducing excess inventory
  • Scaling opensearch cluster

▲Active Projects

  • Box filling algorithms
  • Inventory forecasting
  • Grocery personalization algorithms
  • Recipe coverage analysis framework
  • Dynamic recipe generation system
  • Internal recipe creation tooling
  • Landed cost analysis
  • Internal control strengthening
  • Inventory close process improvement
  • Hybrid search platform development

Hiring Activity

Accelerating8 roles · 8 in 30d

Department

Data
2
Engineering
2
Finance
1
Marketing
1
Ops
1
Product
1

Seniority

Senior
8
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About Hungryroot

Hungryroot is a grocery delivery and wellness platform founded in 2015 that uses AI to personalize food and supplement recommendations based on user goals, budget, and lifestyle. The business operates across three linked problems: (1) understanding and predicting individual consumer preferences via recipe and product recommendations, (2) dynamically generating recipes that match those preferences, and (3) operationally solving the supply chain—how to fill boxes, forecast demand, manage inventory, and calculate landed costs. The company is based in New York with 201–500 employees and operates in the United States and Canada.

HeadquartersNew York, New York
Company Size201–500 employees
Founded2015
Hiring MarketsUnited States, Canada

Frequently Asked Questions

What tech stack does Hungryroot use?

Python, Go, TypeScript backend; PyTorch and scikit-learn for ML; Databricks for data; LangChain and Vercel AI SDK for LLM features; Gurobi and CPLEX for optimization; Looker for analytics; NetSuite for ERP; Dayforce for HR; Datadog and Sentry for monitoring.

What is Hungryroot working on?

Box-filling and inventory-forecasting algorithms, dynamic recipe generation, grocery personalization engines, recipe coverage analysis, hybrid search infrastructure, and supply-chain optimization including landed cost analysis and inventory management.

How this profile is built

Hungryroot's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.