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CommerceIQ Tech Stack

AI-powered ecommerce management platform for marketplace sellers

Software Development Mountain View, California 201–500 employees Founded 2012 Privately Held
commerceiq.ai LinkedIn

CommerceIQ operates an AI-driven ecommerce platform serving 2,200+ brands across major marketplaces. The tech stack reveals a company mid-transformation: deep ML infrastructure (PyTorch, TensorFlow, Hugging Face, Databricks, SageMaker, Vertex AI) paired with active adoption of distributed training tools (DeepSpeed, PyTorch Lightning, Ray), signaling a shift toward agentic AI products. Engineering-heavy hiring (26 of 46 open roles) focused on senior and manager-level roles reflects the challenge of building new ML-powered features while scaling scheduling and data infrastructure to handle massive marketplace datasets.

Tech Stack 77 technologies

Core StackJava Python AWS Figma Cursor Apache Spark Kubernetes PyTorch TensorFlow Hugging Face Databricks SageMaker Vertex AI Node.js React PostgreSQL The Trade Desk JavaScript TypeScript GCP Azure LoRA Azure Machine Learning DeepSpeed PyTorch Lightning Ray Amazon Advertising Amazon DSP Instacart Amazon Marketing Cloud+47 more
AdoptingCursor DeepSpeed PyTorch Lightning Ray

What CommerceIQ Is Building

◆Challenges

  • Scaling scheduling system for massive data
  • Improving ecommerce performance
  • Optimizing advertising spend
  • Ensuring customer adoption
  • Driving profitable revenue growth
  • Scaling ml infrastructure
  • Identifying bottlenecks in architecture
  • Meeting cost and scale slas
  • Scaling ml-powered features
  • Integrating data from disparate sources

▲Active Projects

  • Feature development
  • Multi-cloud deployments
  • Disaster recovery for services
  • Crawl platform
  • Build agentic ai products and capabilities from the ground up
  • Help shape and implement the core architecture of a new product
  • Model management and performance monitoring tools
  • New scheduling system iteration
  • Ai platform for commerce
  • Ai agents for content, media, and sales

Hiring Activity

Accelerating45 roles · 45 in 30d

Department

Engineering
26
Support
7
Data
5
Ops
3
Sales
3
Product
2

Seniority

Senior
20
Mid
11
Manager
5
Director
3
Junior
3
Lead
3
Intern
1

Notable leadership hires: Director of Engineering, Account Director

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About CommerceIQ

CommerceIQ provides an AI-powered platform for brands to optimize their presence and performance across major ecommerce marketplaces and retail channels. The platform integrates data from a global network of 900+ retailers, helping brands make pricing, inventory, and advertising decisions. Core capabilities span digital shelf optimization, retail media ROI tracking, and incremental sales attribution. The company serves primarily mid-market and enterprise consumer goods and food & beverage brands seeking to consolidate fragmented marketplace operations and unlock data-driven selling strategies.

HeadquartersMountain View, California
Company Size201–500 employees
Founded2012
Hiring MarketsCanada, India, United Kingdom, United States

Frequently Asked Questions

What is CommerceIQ's tech stack?

CommerceIQ uses Java, Python, Node.js, and React for core services. ML infrastructure includes PyTorch, TensorFlow, Hugging Face, Databricks, and cloud-native ML platforms (SageMaker, Vertex AI, Azure ML). Data layer runs on PostgreSQL and Apache Spark. Recently adopting DeepSpeed, PyTorch Lightning, and Ray for distributed training.

What is CommerceIQ building?

Current projects include agentic AI products, ML model management tools, a new scheduling system iteration, disaster recovery infrastructure, and a crawl platform. Architecture priorities include scaling ML-powered features and integrating data from disparate marketplace sources.

How this profile is built

CommerceIQ'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.