Bringg

HQ
Chicago
Total Offices: 5
180 Total Employees
70 Product + Tech Employees
Year Founded: 2013
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Bringg Offices

Bringg is headquartered in Chicago and has 5 office locations.

Hybrid Workplace

Employees engage in a combination of remote and on-site work.

Typical time on-site: Flexible

U.S. Office Locations

HQ Chicago

Global Office Locations

HQ Tel Aviv-Yafo Kyiv London Warsaw
HQ

Chicago

We are located in the heart of the city - The Loop! Our office is surrounded by vibrant city views, historic architecture, incredible dining, and shopping (plus, you're just a few steps away from hopping on the bus or train!).

HQ

Tel Aviv-Yafo

132 Derech Menachem Begin, Tel Aviv-Yafo, Israel

Jobs At This Office

Kyiv

Kniaziv Ostrozkykh street, 8 - Creative State of Arsenal, Kyiv, Ukraine

London

307 Euston Rd., London, United Kingdom, NW1 3AD

Warsaw

Tadeusza Czackiego 15/17, Warsaw, Poland

Recently posted jobs

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UX Design Lead

YesterdaySaved
In-Office
Tel Aviv, ISR
Cloud • Enterprise Web • Logistics • Software
Lead ownership of Bringg's design system and AI-driven design workflows. Build prompting guides and templates for PM-led design, review high-stakes flows, coach five PMs asynchronously, and define UX standards to ensure consistent product quality.
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Bringg

Senior UI/UX Designer

5 Days AgoSaved
Remote
EE
Cloud • Enterprise Web • Logistics • Software
Lead the end-to-end UI/UX redesign of a Salesforce application, transitioning its legacy front end to Lightning Web Components. Create wireframes, prototypes, design specifications, component libraries, and design guidelines aligned with SLDS. Collaborate with Salesforce engineers, product managers, QA, customer success, and customers to deliver a scalable enterprise SaaS experience supporting AI workflows.
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Bringg

Data Scientist - Maternity Leave Cover (Long-Term)

13 Days AgoSaved
In-Office
Tel Aviv, ISR
Cloud • Enterprise Web • Logistics • Software
Research, prototype, and validate ML solutions; own end-to-end model lifecycle including production deployment, drift monitoring, and retraining; explain models to engineers, product, and stakeholders; identify new ML opportunities and push models into production.
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