Soma Capital Portfolio Jobs

Planning Intern



San Francisco, CA, USA
Posted on Thursday, January 25, 2024

Who We Are

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a private company founded in 2020 and backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit

Job Description

We are looking for a Planning Engineer who knows how to build best-in-class planning system designs for autonomous driving systems in structured, low-speed environments.

In this role, you'll own, revise, and scale a core planning module at a fast-paced, early-stage startup. Leveraging your experience building production-grade planners, you’ll propel the AeroVect Driver to handle various driving scenarios, achieving category-defining vehicle autonomy for the airport operational design domain.

Your scope will include leading the system design and implementation of key improvements to the current AeroVect planner including the global mission planner, behavior planner, and motion planner.

The opportunity offers a technical, hands-on engineer the chance to help develop a market-defining enterprise product that combines autonomous vehicle technology with a robotics-as-a-service (RaaS) business model. This role reports to our VP of Engineering and works closely with the autonomy engineering team.

What You’ll Do

  • Define, implement, and own hands-on improvements to upgrade the core planner module, targeting milestones, growing the team, and working with internal/external partners — expect to spend 80% of your time performing hands-on development, with the remaining 20% leading the planning module roadmap, including directing schedule, removing obstacles, and coaching the team to hit aggressive milestones.

  • Closely work with a team of engineers bringing up all components necessary for reliable autonomous driving in the airside environment, including vehicle corridors and the apron.

  • Design, implement, test, and support all aspects of ground vehicle autonomy, including planning, prediction, perception, localization, controls, and infrastructure subsystems

  • Qualify all subsystems using objective measures, with an eye to functional safety and systems engineering best practices

  • Collaborate with vehicle engineering to create an integrated system, including sensor/compute selection and integration


Minimum Qualifications

  • Prior background (academic or industrial) in the development of planning modules for autonomous systems

  • Strong theoretical knowledge of & industrial experience in one or more areas of planning: routing, behavior planning, and trajectory generation (e.g., optimization-based or sampling-based)

  • Bachelor’s Degree or Master’s Degree candidate in Computer Science, Math, Electrical Engineering, Mechanical Engineering, Robotics, Physics, or a related field

  • Strong C++ (preferred) or Python programming and algorithmic problem-solving skills

  • Working experience in a Linux based Operating System

  • Experience using the Robot Operating System (ROS) framework and tools like Rviz, rqt, tf, etc.

  • Strong reasoning skills and mathematics background including linear algebra, geometry, calculus, optimization, and probability to name a few

  • Solid engineering background with hands-on design and development experience

  • Experience with field testing autonomous systems

  • Highly collaborative nature and an exceptional communicator

Desired Qualifications

  • MS or Ph.D. in Computer Science, Math, Robotics, or a related field

  • In-Depth understanding of DDS frameworks like ROS/ROS2 or other networking middleware

  • Proven track record of system development and successful deployment of unmanned systems in existing or upcoming products

  • Mastery of Modern C++ (14 and beyond) and safety-critical coding practices (MISRA and ISO 26262 compliance)

  • Prior experiences at an autonomous driving company or an engineering startup.