Job Opportunities API

Latitude AI ( lat.ai ) is building the future of Ford’s autonomy roadmap to make travel safer, less stressful, and more enjoyable for everyone. Bringing this vision to scale, our fully in-house developed hands-free ADAS platform will debut on Ford’s all-new Universal Electric Vehicle in 2027.  When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to redefining the relationship between people and their vehicles for millions of customers. As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif. Meet the team: The Virtual Test Ecosystem (VTE) team is responsible for implementing the tooling used by Latitude to perform simulations (pure virtual scenarios where we can control interactions and sweep over permutations via a descriptive scenario language) and resimulations (rerunning logs collected on-vehicle using an updated version of the autonomy stack). This includes the backend C++ simulation/resimulation frameworks that call the underlying autonomy tasks and Python-based tooling to run this at large scale in the cloud. This infrastructure enables us to do a large portion of testing before the code ever makes it on vehicle, dramatically reducing autonomy developer iteration time and allowing us to perform large-scale safety testing. We work closely and iteratively with autonomy teams to build out new sim/resim features that they need in order to evaluate their new autonomy features. Similarly, we work hand-in-hand with the offboard testing teams who are building out test coverage to ensure they can use our tooling to write the tests they need and to get feedback on how we can make this test creation more efficient. And of course we’re constantly benchmarking and evaluating the efficiency and scalability of our applications in order to reduce runtimes and cost. What you’ll do:  Implement the parser code which takes a definition of a sim scenario, parses it, and plumbs it through so that the backend simulation engine can execute the desired scenario (placing actors in desired locations, coordinating interactions between the actors and AV, etc.) Work closely with the autonomy developers and scenario creation team to understand new requirements (we’re constantly increasing our ODD and implementing new autonomy features), determine the best way to express that in the scenario definition, then implement it. Discuss pain points with simulation users (what’s difficult to express in the scenario definitions, what’s difficult to maintain, what’s confusing when there are errors, etc.) and then propose and implement solutions. Implement mechanisms for allowing key scenario parameters to express a range of values which are then sampled efficiently While the main focus is on tooling related to scenario creation, also provide support related to other backend sim infrastructure updates (how messages flow through the system, how we interact with vehicle logs and maps, etc.) Through your work, you’ll be enabling users to create a rich set of scenarios which validate the safety and comfort of our AV, then running it in a highly scalable cloud environment What you'll need to succeed: Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD) Expertise in modern C++ (C++17) Self-driven to write code that’s efficient, well-tested, well-documented, and conforms to our style guide 3+ years’ experience with developing complex parsing software Stron