Overview
Zendar is looking for a research-oriented Machine Learning Intern (World Modeling and Scene Understanding) to join our Berkeley office. Zendar develops one of the best 360-degree radar-based vehicular perception systems for automotive. We are expanding our autonomy stack toward scene-level world modeling, developing representations that capture occupancy, motion, and temporal evolution of the environment. This work builds on multi-sensor perception (camera, radar, and beyond) and is designed to scale across both the automotive and robotics industries. We are not bogged down by legacy systems, and by joining us you’ll have the opportunity to define and own key components of a next-generation world model that supports reliable, long-horizon autonomy.
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 develop scene-level world models that represent and forecast the occupancy and dynamics of the environment, enabling robust downstream autonomy across automotive and robotics applications.
As an ML Research Intern, you will work on learning-based world models that estimate full-scene occupancy and motion (occupancy-flow) and predict how the scene evolves over time. These models leverage inputs from radar, camera, and other sensors to provide a unified, reusable representation for downstream tasks such as planning and collision avoidance. You will work closely with experienced engineers and researchers to prototype, train, and evaluate these models on large-scale real-world datasets, and gain hands-on exposure to deploying perception models in real-time systems.
This role is ideal for a PhD student who enjoys designing spatio-temporal modeling, and working with real sensor data in autonomy.
What You’ll Do
• Contribute to the design and implementation of scene-level world models for autonomy
• Develop and experiment with occupancy, free-space, and dynamic occupancy / flow representations
• Train and evaluate spatiotemporal deep learning models
• Work with real-world sensor data from radar, camera, and lidar
• Help define evaluation metrics and analyze model behavior over time and across edge cases
What We Look For
• Currently pursuing a PhD in Computer Science, Robotics, Electrical Engineering, or a related field
• Strong interest or prior experience in scene-level world modeling (occupancy, free space, motion, dynamics) and unsupervised or semi-supervised learning techniques.
• Experience (projects, publications, or thesis work) with spatio-temporal modeling.
• Experience working with any real-world sensor data (camera, lidar, radar, or multi-sensor)
• Proficiency with Python and a major deep learning framework (e.g., PyTorch, TensorFlow)
What We Offer
• Opportunity to make an impact at a young, venture-backed company in an emerging market
• Competitive salary of $55 / hour
• 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
Company:
Zendar
Qualifications:
Language requirements:
Specific requirements:
Educational level:
Level of experience (years):
Senior (5+ years of experience)
About Zendar
Zendar develops high-definition radar for autonomous vehicles.
