Zendar builds a radar-centric autonomy stack which makes any vehicle - from cars to robots - autonomous in any environment. With our deep radar DNA, we have architected our solution to put RF sensing at the core of all perception. The result is a system that handles long range, high speeds, and bad weather not as edge cases but as a core strength of the autonomy stack.
Because radars naturally measure both 3D position and velocity for every object in the environment, radar-centric autonomy is extremely compute- and data-efficient. Our autonomous vehicle needs only a few thousand dollars of hardware to make it completely autonomous, making this the cheapest way to build an autonomous vehicle by far.
See a demo of Zendar’s foundational RF perception and driving functions.
To develop this capability we had to build the entire stack in house - from radar sensor hardware to signal processing to multi-modal perception foundation models and path and trajectory planning. As part of a small team, you will have a front-row seat to seeing how a complete autonomy stack is architected and how your engineering decisions improve the ability to navigate autonomously in the real world.
Although AI is central to what we build, our hiring process is intentionally human: every résumé is reviewed by a real person.
The Vehicle Motion Planning & Control team is responsible for behavior and trajectory planning for our autonomous vehicle — deciding where the vehicle goes and how it gets there. The team also owns vehicle control (longitudinal and lateral) and the on-vehicle integration that makes our vehicles drive safely, comfortably, and predictably in the real world. The team's 6-month roadmap is to rapidly unlock new driving behaviors, like Navigate on Autopilot (NoA) on highways.
We are hiring a Software Engineer to join the team and you will own components from algorithm design through real-time C++ implementation, simulation, tuning, and on-vehicle validation. Because the team is small and the surface area is large, this role is ideal for someone with strong software fundamentals, a solid grounding in robotics or controls, and genuine eagerness to see their code move a physical vehicle.
Key Responsibilities:- Design and Build the Motion Planning Stack
- Develop trajectory planning and decision-making algorithms that produce safe, smooth, dynamically feasible motion in dynamic, uncertain environments — including scenarios with noisy or incomplete perception input
- Reason about interactions with other road users and translate desired driving behavior into algorithmic changes across the planning stack
- Develop Vehicle Control Software
- Architect, implement, and validate control and estimation algorithms for the vehicle's longitudinal and lateral dynamics
- Write mission-critical, real-time C++ that runs on-vehicle and on embedded automotive compute
- Integrate with Perception and Platform
- Work closely with our Perception and Software Platform teams to define clean interfaces between perception output, planning, and control
- Support driving-function demos on our vehicles, from bring-up through customer-facing runs
- Test, Measure, and Improve
- Build simulation and analysis tooling in Python and C++ to evaluate planner and controller performance before code ever touches a vehicle
- Define metrics for driving quality and safety, extract insights from field data, and feed them back into development
- Contribute to failure and hazard analyses and implement safety mitigations in planning and control software
- Ability to work from the office in Berkeley, CA, at least from Tuesday to Thursday
- 3+ years of software engineering experience, with production-quality coding skills in modern C++ and Python
- Hands-on experience in motion planning, decision making, or vehicle controls (e.g., optimization-based planning, search methods, optimal control, MPC, probabilistic decision making) on autonomous vehicles, ADAS, or robotic systems
- Solid foundation in linear algebra, geometry, statistics & probability, and vehicle dynamics
- Experience taking features from design through real-world deployment — not just prototypes
- Ability to break down complex, ambiguous problems into well-defined technical solutions
- Somebody with solid opinions based on experience, yet open-minded and flexible to find the best solution for the situation
- Experience deploying planning or control software on real vehicles (AV, ADAS features like ACC, AEB, lane keeping / lane changing)
- Experience with real-time and embedded systems and RTOS
- Experience with ML-based approaches to planning (imitation learning, RL, learned cost functions) alongside classical methods
- Opportunity to make an impact at a young, venture-backed company in an emerging market
- Collaboration with smart and motivated engineers and ability to execute your vision in a high impact role
- Competitive salary ranging from $160,000-180,000 annually depending on experience
- Performance based Bonus
- Benefits including medical, dental, and vision insurance, flexible PTO, and equity
- Daily catered lunch and a stocked fridge in the Berkeley office
Zendar is committed to creating a diverse environment where talented people come to do their best work. We are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Zendar participates in E-Verify
Skills Required
- Ability to work from the office in Berkeley, CA at least Tuesday to Thursday
- 3+ years software engineering experience with production-quality coding in modern C++ and Python
- Hands-on experience in motion planning, decision making, or vehicle controls on autonomous vehicles, ADAS, or robotic systems
- Solid foundation in linear algebra, geometry, statistics & probability, and vehicle dynamics
- Experience taking features from design through real-world deployment
- Ability to break down complex, ambiguous problems into well-defined technical solutions
- Experience deploying planning or control software on real vehicles (AV, ADAS features like ACC, AEB, lane keeping/lane changing)
- Experience with real-time and embedded systems and RTOS
- Experience with ML-based approaches to planning (imitation learning, RL, learned cost functions)
What We Do
At Zendar, we are building the highest resolution automotive radar in the world. Our product combines the benefits of radar, such as long-range and all-weather operation, with the resolution of lidar. We want to make autonomous driving safe and accessible for everyone.








