Serve Robotics (NASDAQ:SERV) develops advanced, AI-powered, low-emissions sidewalk delivery robots that endeavor to make delivery sustainable and economical. Spun off from Uber in 2021 as an independent company, Serve has completed tens of thousands of deliveries for enterprise partners such as Uber Eats and 7-Eleven. The company has scalable multi-year contracts, including a signed agreement to deploy up to 2,000 delivery robots on the Uber Eats platform across multiple…
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Serve Robotics develops advanced, AI-powered, sidewalk delivery robots that make delivery sustainable and economical
Description complète de l’entreprise
Serve Robotics (NASDAQ:SERV) develops advanced, AI-powered, low-emissions sidewalk delivery robots that endeavor to make delivery sustainable and economical. Spun off from Uber in 2021 as an independent company, Serve has completed tens of thousands of deliveries for enterprise partners such as Uber Eats and 7-Eleven. The company has scalable multi-year contracts, including a signed agreement to deploy up to 2,000 delivery robots on the Uber Eats platform across multiple U.S. markets.
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Abonnés LinkedIn
29 393
Personnes associées sur LinkedIn
409
Bureaux déclarés
Los Angeles, CA 90046, US
San Francisco, CA 94122, US
Miami, Florida 33130, US
Dallas, TX 75204, US
Catégories d’activité
Information Technology
Robotics
Food Delivery
Logistics
Artificial Intelligence (AI)
Autres noms enregistrés
Serve Robotics
Le profil indique une agence de recrutement
Non
Investissement total déclaré
544 000 000
La devise et la date d’observation ne sont pas fournies; ce n’est ni une valorisation actuelle ni une ronde de financement.
Secteur
Technology, Information and Internet
Taille
51-200 employees
Siège social
Los Angeles, CA
Type d’organisation
Public Company
Fondée en
2021
Serve Robotics a 5 offres ouvertes au Canada en date du 9 novembre 2026. Principaux lieux : Calgary, Vancouver et Toronto.
Serve Robotics: Serve Robotics (NASDAQ:SERV) develops advanced, AI-powered, low-emissions sidewalk delivery robots that endeavor to make delivery sustainable and…
6+ ansCandidates need 6+ years of product management experience shipping software products, experience with operationally complex environments, and strong analytics and API fluency. Practical use of AI-enabled tools and LLMs for data analysis is valued.
Serve Robotics: Serve Robotics (NASDAQ:SERV) develops advanced, AI-powered, low-emissions sidewalk delivery robots that endeavor to make delivery sustainable and…
5+ ansCandidates need a bachelor's degree or equivalent practical experience, 5+ years of professional software engineering including production C++17 work, and embedded Linux experience. They also need concurrency, real-time or safety-related systems experience, and strong communication skills.
C++, Linux, NVIDIA Jetson, Protocol Buffers, FlatBuffers, Cap'n Proto
Serve Robotics: Serve Robotics (NASDAQ:SERV) develops advanced, AI-powered, low-emissions sidewalk delivery robots that endeavor to make delivery sustainable and…
15+ ans8+ gestionCandidates need 15+ years in IT infrastructure and operations, including 8+ years in leadership, and experience running complex distributed environments at a high-growth tech company. Deep knowledge of networking, cloud, identity management and enterprise systems is required, plus experience at a public company and strong communication and vendor management skills.
Serve Robotics: Serve Robotics (NASDAQ:SERV) develops advanced, AI-powered, low-emissions sidewalk delivery robots that endeavor to make delivery sustainable and…
5+ ansCandidates need a Master's or PhD in a technical field and at least 5 years of experience training and deploying machine learning models in production. Strong Python skills and hands-on experience training models across multiple GPUs or nodes are required.
Serve Robotics: Serve Robotics (NASDAQ:SERV) develops advanced, AI-powered, low-emissions sidewalk delivery robots that endeavor to make delivery sustainable and…
Candidates need product or engineering experience with data infrastructure in autonomous vehicles, automotive or robotics, plus experience building production ML Ops pipelines. Familiarity with training datasets, model evaluations and active learning is also required.