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Nimble Robotics

AI-powered robotic fulfillment for eCommerce logistics

Member of Technical Staff

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • A Ph.D. in Robotics or Computer Science.
  • Experience training deep learning models for robotic manipulation or mobility.
  • Experience working with real robotic hardware.
  • Experience training models in simulation and developing simulation environments.
  • Experience collecting custom datasets.
  • Experience training on open-source datasets.
  • A strong track record of publishing papers and/or deploying real-world applications.
  • Experience with system architecture, design, and development.
  • Ability to work extended hours and weekends as needed.
  • Ability to work in San Francisco.

Responsibilities

  • Develop and train Vision-Language-Action Models and generalist visuomotor policies to automate thousands of tasks across the supply chain.
  • Develop data collection pipelines.
  • Design data annotation and labeling.
  • Support implementation of models into production systems.

About the Company

Nimble Robotics

AI-powered robotic fulfillment for eCommerce logistics

Nimble Robotics uses artificial intelligence to optimize eCommerce logistics and supply chains, coordinating fulfillment and inventory planning to speed deliveries and improve accuracy. Its system includes robotic fulfillment hardware that handles items that fit in a bin, with oversized items processed manually, and works via plug‑and‑play integrations with Shopify, Netsuite, and Skubana on a pay‑as‑you‑go, no-upfront-capex model plus pilot options. It differentiates itself by combining AI‑driven optimization with robotic fulfillment and a hands‑off support model backed by engineers and leaders from robotics and logistics, plus flexible pilots. The goal is to help brands—from startups to Fortune 500s—scale fulfillment efficiently, reduce delivery times, and boost sales and customer satisfaction without upfront costs.

Company size
201-500
Company stage
Series C
Total funding
$221M
Headquarters
San Francisco, CA
Founded
2017

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