Key technologies and capabilities for this role
Common questions about this position
The position is hybrid and based in Los Angeles, Austin, or New York City.
This information is not specified in the job description.
Candidates need experience building and deploying robotic systems, expertise in CAN bus for debugging and interfaces, proficiency in computer vision pipelines like VO and object tracking, and familiarity with reinforcement learning and simulation environments.
Nominal is a venture-backed company building software and data solutions for testing complex systems like drones, robots, rocket engines, and satellites, backed by investors such as General Catalyst, Founders Fund, and Lux Capital, with work in commercial and government aerospace and defense.
A strong candidate is an experienced roboticist who has built and deployed systems, with deep expertise in CAN bus, computer vision perception pipelines, and reinforcement learning with simulations.
Software tools for engineering hardware systems
Nominal.io provides software tools designed specifically for engineering teams working with complex hardware systems. Their platform allows these teams to test and deploy hardware systems significantly faster than traditional methods, making it particularly beneficial for industries such as aerospace, defense, energy, and telecommunications, where hardware performance is critical. The platform consolidates data from various sources, enabling engineers to monitor and analyze their systems effectively in a secure environment. Unlike many competitors, Nominal.io focuses on a niche market with high demands for reliability, offering a software-as-a-service (SaaS) model that ensures clients have continuous access to the latest features. The company's goal is to enhance the resilience and performance of hardware systems, positioning itself as a key partner for engineering teams looking to improve their deployment processes.