At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.
The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.
Who We Are
We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.
Data is an integral part of Serve’s autonomy stack. As of EOY 2025, Serve has 2000 actively deployed robots making real world deliveries across numerous US cities. ‘Autonomy Data Flywheel’ is an internal Data product initiative that leverages on this large scale of real world robots and super-charges our End-End AI model development. It covers the entire data lifecycle starting with the data offloading infrastructure on edge, depots, and meeting the engineering needs of training, testing & validation.
Responsibilities
Build and drive roadmap for the Autonomy Data Flywheel
Draft requirements and ensure delivery for all consumers of the data including End-End AI, Perception, Safety and other teams.
Work with engineering teams to set and achieve targets for both quality and quantity KPIs
Define and maintain Data Diversity metrics for maximizing scenario coverage on Sidewalk ODD(Operational Design Domain)
Cross functional initiatives with Operations and IT teams to drive depot and cloud infrastructure work.
Support Data pipelines so that we are retaining the right data without impacting safety and day to day operations
Qualifications
Product/Engineering Experience for data infrastructure in AV/Automotive or Robotics/Edge AI industries
Experience building production level ML Ops pipelines
Fluent with training datasets and evals for AI models
Preferred: Experience with data infrastructure at Edge/Depot (E.g. NAS infra) and Cloud
Experience with ML Ops, targeted and active learning approaches
*Please note: The listed base salary range applies to candidates based in the San Francisco Bay Area. Compensation may vary depending on location, experience, and role alignment. We are open to qualified candidates working remotely within the United States and Canada
USA - ALL: $200k - $245k USD
Canada - ALL: $175k - $215k CAD