Who we are: Glydways is reimagining what public transit can be. We believe that mobility is the gateway to opportunity—connecting people to housing, education, employment, commerce, and care. By making transportation more accessible, affordable, and sustainable, we empower communities to thrive and unlock economic and social prosperity. Our mission is to revolutionize transit with a solution that delivers high capacity, exceptional user experiences, unmatched affordability, and minimal environmental impact. The Glydways system is a groundbreaking network of carbon-neutral, interconnected transit pathways powered by standardized autonomous vehicles on dedicated roadways. Operating 24/7 with on-demand access, it offers personalized and efficient mobility—without the burden of heavy upfront infrastructure costs or ongoing taxpayer subsidies. With Glydways, we’re building more than a transportation system; we’re creating a future where everyone, everywhere, has the freedom to move. Meet the team: The Glydways perception team is responsible for designing and implementing a perception system that includes data fusion from state-of-the-art sensors (e.g., LIDAR, RADAR, High definition cameras, Ultra-wide-band radios, etc.) and robust detection, classification, and tracking of any and all obstacles that could present a hazard to the vehicle (Glydcars) in the system. The perception system for Glydways will reason about information from each Glydcar and from regularly spaced sensor pods monitoring the road network. The perception team plays a vital role within the Autonomy Software engineering team. The team’s deliverables include: - Documenting a detailed design for enacting a safe system that can be certified by public transportation authorities. - Implementing said design on mature prototype vehicles in demonstrations to customers, potential customers, and investors. - Expanding the design to include fail-operational capabilities that extend the overall system to safely give our customers a more comfortable experience. - Managing data collection, autonomy testing, and milestone demonstration events that showcase the system’s maturing capabilities, leading to a production system. Team members may work remotely and must be self-motivated. Roles & Responsibilities: - Design, implement, and maintain high-performance C++ modules at the boundary of detection like tracking, and prediction. - Integrate outputs from multiple sensors(camera, lidar, radar, map) into EKF-based tracking and fusion systems. - Own metrics, evaluation pipelines, and tooling to measure detection and tracking quality and catch regressions at scale. - Define and maintain clear interfaces between perception, tracking, and planning modules with a focus on robustness and debuggability. - Develop simulation, log-replay, visualization, and offline analysis workflows to improve test coverage before on-vehicle deployment. Knowledge, Skills and Abilities: - Strong proficiency in modern C++ (C++14/17 or newer). - Production experience with state estimation and multi-sensor fusion, including EKF/UKF, motion models, data association, and uncertainty handling. - Experience designing metrics and evaluation frameworks for real-time, ML-driven robotics systems. - Strong debugging skills across distributed and asynchronous pipelines, using logs and metrics to drive root-cause analysis. - Excellent verbal and written communication skills. Glydways provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Role Description Moonshot Aerospace is seeking a Staff Navigation Engineer to lead spacecraft navigation system design and analysis. Initial assignments will support navigation system development for lunar lander, cislunar orbital transfer vehicle (OTV), and related spacecraft programs for commercial and government customers, including the Human Landing System (HLS) and Commercial Lunar Payload Services (CLPS). This is a navigation-focused position requiring deep experience in Kalman filter design, spacecraft state estimation, and navigation sensor integration for cislunar and planetary environments. The engineer will serve as a technical authority on navigation architecture and will be expected to independently drive navigation system development from requirements through flight operations support. Multiple experience levels are available, and responsibilities will scale with demonstrated capability. - Design, develop, and tune navigation filters (EKF) for lunar lander, OTV, and related spacecraft applications - Define navigation system architecture for cislunar and planetary mission phases including sensor selection, measurement models, and filter configuration - Develop navigation error budgets and perform covariance analysis for orbit determination and powered descent - Implement navigation algorithms in flight software and support SWIL/HWIL integration and test - Perform Monte Carlo analysis to verify navigation performance under dispersed conditions across cislunar and descent phases - Develop and validate sensor models (IMU, star tracker, GPS/GNSS, LiDAR, optical navigation camera) for lunar and cislunar environments - Support navigation sensor testing, calibration, and characterization - Contribute to technical documentation, peer reviews, and customer presentations - Collaborate across GN&C, flight software, and systems engineering teams Qualifications - U.S. Citizenship and ability to obtain and maintain a security clearance - B.S. in Aerospace Engineering, Electrical Engineering, Physics, or related field - 5+ years of professional experience in spacecraft navigation system design and analysis - Demonstrated experience designing and implementing Kalman filters for spacecraft applications - Experience with navigation sensor integration and testing (IMU, star tracker, GPS, LiDAR) - Strong programming skills in C/C++, Python, and MATLAB - Experience with spacecraft dynamics and orbital mechanics - Familiarity with real-time software systems and flight software integration - Effective written and verbal communication skills Preferred Qualifications - M.S. or Ph.D. in Aerospace Engineering, Electrical Engineering, Physics, or related field - 8+ years of navigation engineering experience on spacecraft programs - Lunar or cislunar navigation experience, including orbit determination and powered descent navigation - Terrain Relative Navigation (TRN), optical navigation, or image-based navigation for lunar surface operations - Experience with navigation analysis tools (MONTE, GEONS, ODTK, or equivalent) - Multi-sensor fusion and relative navigation for rendezvous and proximity operations - Hardware-in-the-loop (HWIL) navigation sensor integration and test - Experience with NASA Trick simulation framework or equivalent - Conference publications or technical papers in spacecraft navigation - Launch vehicle or satellite navigation experience

• help our customers love Rerun • be the primary technical interface between Rerun and a set of customers, from demo to signed contract and through deep production use • ingest data from physical systems, curate datasets, and convert into training datasets • build reference projects for embodied AI use cases such as imitation learning pipelines, sim-to-real setups, and evaluation frameworks • running demos and building engineer-to-engineer trust alongside our founders based on machine learning work • support onboarding customers onsite and remotely, with anticipated 30% travel • mapping customer needs and one-off solutions to evolve our roadmap

• Build, deploy, and maintain automations on a modern GUI-based RPA platform from day one • Develop reusable components and structured workflows that are built to scale • Map current-state processes clearly before building and keep documentation current as things evolve • Diagnose and resolve complex bot failures end to end without escalating prematurely • Connect automations to external systems using REST APIs and webhooks