Staff Engineer (Trajectory Planning)

Oxa is enabling the transition to self-driving vehicles through an initial focus on the most commercially advanced sector; the autonomous shuttling of goods and people.

We are home to some of the world’s leading experts on autonomous vehicles, creating solutions such as Oxa Driver, equipping vehicles with full self-driving functionality; Oxa MetaDriver, using Generative AI to accelerate and assure the safety of deployments; and Oxa Hub, a set of cloud-based offerings for autonomous fleet management. Our technology is being deployed across the UK and the U.S, and we’re partnering with a fast-growing ecosystem of operators, vehicle OEMs and equipment makers serving autonomous transportation globally as it advances.

Based in Oxford, and with offices in Canada and the U.S, Oxa was founded in 2014 and is  growing rapidly (350+ ‘Oxbots’ to date). Our purpose is to change the way the Earth moves, through an uncompromising focus on safety, efficiency and explainability of our AI approaches. The company has attracted $225 million from leading investors so far, with $140 million raised in the last Series C funding round in January 2023.

Your Team

You will join our growing Planning Team, where we design, implement, test, and deploy the Engine that defines the behaviour and motion of Oxa’s Autonomous Vehicles (AVs), based on our understanding of the environment.

Your Role

As a Staff Engineer in Trajectory Planning, you will be responsible for designing, implementing, testing, and deploying the trajectory planning software that generates the trajectories for the AV. Specifically, this role will focus on building a robust and efficient trajectory generation approach to achieve the desired AV maneuvers in a comfortable, human-like, and safe manner for different on-road and off-road applications. You will work closely with other teams in a highly cross-functional development environment. 

In this role, you will:

• Lead the development, integration, and deployment of trajectory planning software that robustly and efficiently generates AV trajectories, including off-the-shelf solver evaluation and custom solver implementation.
• Take ownership of the trajectory planning approach and architecture with a focus on high quality functionality and APIs that allow the trajectory planner component to be used as a building block for various on-vehicle applications.
• Promote a cross-functional development style, working closely with other teams to realise the desired AV manoeuvres as well as their smooth, comfortable, and precise execution.
• Create appropriate metrics and tools to measure and benchmark the performance of the trajectory planner deployed on various AV platforms.
• Own the engineering lifecycle, including scoping, design, implementation, testing, deployment, and maintenance of your team's work.
• Influence the technical strategy within the Planning Team, ensuring alignment with your counterparts in other teams.
• Document and train others on your team's work, focus on improving features, and understand the business and customer value of your team's work.

• Spearhead hiring and onboarding at scale by defining role responsibilities and requirements, leading interviews, engaging in recruiting outreach for your team, and mentoring and developing new team members.
• Positively impact product quality, customer experience, and maintainability, and identify projects that improve team processes and solutions.

Requirements

What you need to succeed:

• PhD in related field (Mech Eng, Aerospace, Comp Science, Robotics, Applied Mathematics) with 3+ years of industry experience is desired
• MS in related field (Mech Eng, Aerospace, Comp Science, Robotics, Applied Mathematics) with 5+ years of industry experience is acceptable
• Extensive hands-on experience of optimisation-based trajectory planning and control applications to autonomous driving.
• Deep practical understanding of nonlinear optimisation techniques

• Experience with different trajectory planning problem formulations
• Prior tech lead experience in a software development team focused on trajectory optimisation or vehicle/robot control (preferably within autonomous driving), guiding and mentoring team members.
• Strong C++ and Python software development skills, including modern C++ algorithm development and deployment in a production environment.
• Familiarity with modern software engineering practices, including automated testing and continuous integration.
• Extensive knowledge of vehicle kinematics and dynamics

• Experience with sampling-based trajectory planning approaches