Description
The company is developing state-of-the-art autonomous vehicle software for our purpose-built vehicle.
The Robot Data Visualization team owns one of the most critical and widely used internal engineering platform suites at the company. Our team builds and scales tools that span the entire spectrum of autonomous data visualization: from single-vehicle deep introspection tools (similar to Webviz or RViz) to fleet-level visualization platforms (similar to kepler.gl or Deck.gl).
These web applications serve as the primary lens into autonomous vehicle behavior, enabling engineers across perception, prediction, planning, and systems safety to analyze how our vehicles make decisions in real-time and post-mission scenarios.
We are seeking an Engineering Manager to lead and scale this multi-product engineering team. In this role, you will define product and technical strategy across both single-vehicle and fleet-level visualization domains, mentor high-performing engineers, and push browser execution limits to deliver fast, highly usable, and scalable tools. Here’s a video of our team’s work in action, featuring frame-accurate scene rendering using a multi-widget layout: https://shorturl.at/ewXhT
In this role, you will:
Leadership & Team Growth : Lead, mentor, and grow a team of software engineers specializing in frontend graphics (TypeScript, WebGL, Three.js) and high-performance backend systems (C++)
Product & Technical Vision : Own the technical roadmap across two primary product lines - deep single-vehicle introspection tools and fleet-wide analytics platforms
Push Web & Performance Limits : Architect strategies to push browser performance boundaries, handling complex 3D rendering, time-series data, video streaming, and multi-layered map assets without sacrificing client-side responsiveness
Usability & Capability Expansion : Drive continuous improvements in system usability, expanding capability suites so internal engineering users can quickly diagnose edge cases and evaluate fleet performance
Cross-Functional Collaboration : Partner closely with autonomy, safety and infrastructure teams to convert complex debugging workflows into intuitive visualizations
Engineering Culture : Foster an inclusive, high-impact culture focused on technical excellence, quality, and continuous mentorship