Senior Robotics Engineer – Path & Trajectory Planning

About the position Zendar is looking for a robotics engineer with a focus on path planning and trajectory prediction to join our Berkeley office. Zendar develops one of the best vehicular perception systems for automotive based on a 360-degree radar/camera system. Now we are expanding our capabilities to deliver full driving functions. We are not bogged down by legacy systems and by joining us, you have the opportunity to define and own the driving system. About Zendar: Autonomous vehicles need to be able to understand the world around them not only in bright daylight, but also at night, when it is foggy or rainy, or when the sun is shining right in your face. At Zendar, we make this possible by developing the highest-resolution, most information-rich radar in the world. What makes radar powerful - its long wavelength which makes it robust to all sorts of weather and lighting conditions - also makes it really challenging to work with. We have used our deep understanding of radar physics to build radar perception models that bring a rich and complete understanding of the environment around the AV from free space to object detections to road structure. Check out what our technology can do here - all produced with only radar information, no camera and no lidar! Zendar has a diverse and dynamic team of hardware, machine learning, signal processing and software engineers with a deep background in sensing technology. We have a global team of 60, distributed across our sites in Berkeley, Lindau (Germany), and Paris. Zendar is backed by Tier-1 VCs, has raised more than $50M in funding and has established strong partnerships with industry leaders. Your Role: Zendar’s Semantic Spectrum perception technology extracts a rich scene understanding from radar sensing. Our next goal is to build an AV planner which can use this information to deliver more reliable operation in any weather and lighting, and faster responsiveness when operating at high speeds. This will demonstrate how more informative radar sensing, fused with other sensor modalities, can solve hard challenges in AV deployment on freeways and in challenging weather conditions. We are seeking an experienced Robotics Engineer specializing in path and trajectory planning to join our engineering team. In this role, you will develop and optimize motion planning algorithms to perform highway Navigation on Autopilot (NoA) and eventually scale to city. The ideal candidate will have deep expertise in motion planning theory, optimization techniques, and real-time algorithm implementation. Being the first path planner engineer on the team, you will take significant ownership of the design and implementation of our path planning and trajectory prediction pipeline. This is an ideal position for an engineer who enjoys building path planning systems and validating them in real-world driving scenarios. In this role you will have a close communication and collaboration with the platform, machine learning and perception teams. You will work with our real-world dataset of tens of thousands of kilometers collected in multiple continents and geographies. We also have a test vehicle with actuation enabled which serves as a test platform for all planning and driving functions - today it can do adaptive cruise control (ACC), but your goal would be to expand those capabilities!

Responsibilities

• develop and optimize motion planning algorithms to perform highway Navigation on Autopilot (NoA) and eventually scale to city
• design and implementation of our path planning and trajectory prediction pipeline

Requirements

• Proficiency with Python and C++
• 3+ years of experience in motion planning, path planning, or trajectory optimization
• Hands-on experience on designing and implementing of path planning and trajectory prediction models in relevant fields including robotics and

ADAS

• Familiarity with professional software development tools, such as source control (git), unit testing, and profiling
• Strong communication and cross-functional collaboration skills

Nice-to-haves

• Experience with Model Predictive Control (MPC) or other predictive planning techniques
• Knowledge of machine learning approaches for motion planning (learning-based planners, neural motion planning)
• Good understanding of challenges in machine learning pipeline design such as data collection and processing, model test and evaluation

Benefits

• Opportunity to make an impact at a young, venture-backed company in an emerging market
• Competitive salary ranging from $140,000-$190,000 annually depending on experience
• Performance based Bonus
• Benefits including medical, dental, and vision insurance, flexible PTO, and equity
• Hybrid work model: in office 3 days per week from Tuesday to Thursday, the rest… work from wherever!
• Daily catered lunch and a stocked fridge (when working out of the Berkeley, CA office)

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