Zendar is looking for a Sensor Fusion & Localization Engineer to join our Lindau am Bodensee office. We are deploying a 360-degree radar-based perception system and extending it toward full-stack autonomy through early fusion of camera and radar data. You will work on localization mapping calibration and multi-sensor fusion algorithms that allow autonomous systems to operate robustly across automotive and robotics domains.

This is a unique opportunity to join a team that is not bogged down by legacy code. You will define own and build a next-generation perception stack that enables reliable autonomy at scale.

About Zendar:

Zendar is building perception for physical AIgiving engineers a strong foundation for creating world-class robotics applications. At Zendar youll work on perception foundation models that enable robots to understand and interact with their environments across a wide range of industries.

Zendar pioneered RF perception that delivers a vision-like semantically segmented understanding of the environmentrunning on embedded automotive systems using only radar data. This RF perception forms the backbone of Zendars next-generation foundation models which are built around early fusion of RF and vision data.

This architecture inverts the traditional perception stack. Instead of treating RF signals as secondary Zendars models combine visions high angular resolution with RFs strong temporal and spatial understanding at the earliest stages of perception. The result is a system that sees farther remains robust to occlusion and adverse weather and operates far more efficiently than vision-only or lidar-based approaches.

See a demo of Zendars foundational RF perception

At Zendar youll work at the cutting edge of autonomous mobility and roboticsadvancing foundation models that will power the next generation of physical AI systems. Youll work with large-scale real-world multi-modal datasets composed of synchronized and calibrated radar camera and lidar data collected across multiple continents.

Our team brings together deep expertise across hardware signal processing machine learning and software engineering with decades of experience in sensing and perception. We are a global team with offices in Berkeley Lindau (Germany) and Paris (France). Zendar is well-funded by leading Tier-1 venture capital firms and has established strong industry partnerships.

Although AI is central to what we build our hiring process is intentionally human: every resume is reviewed by a real person.

Your Role:

As a Sensor Fusion & Localization Engineer in Lindau you will design and implement the state estimation framework behind Zendars next-generation autonomy stack. You will work across radar vision and inertial sensing to develop precise robust and efficient algorithms for localization odometry mapping and calibration.

You will have direct access to raw spectral radar data and the opportunity to treat radar as a primary sensor in robotics state estimation.

Why this role is exciting:

• Ownership: You will drive architectural decisions making rigorous tradeoffs between approach A vs. B.
• Scale: You will work with a real-world dataset covering tens of thousands of kilometers across multiple continents.
• Impact: You will see your work validated on real vehicles bridging the gap between research and production

What Youll Do:

• Architect a Multi-Sensor State Estimation System:
  • Own the design and implementation of a multi-sensor robotics and state estimation framework.
  • Develop tightly coupled fusion architectures for streaming camera radar and IMU data with an emphasis on real-time performance robustness and production scalability.
• Deliver Production-Ready Algorithms:
  • Multi-sensor SLAM and localization
  • High-precision online calibration
  • Radar-camera-IMU sensor fusion
  • Navigation for autonomous vehicles
• Drive Reliability:
  • Target four nines reliability behavior in defined conditions focusing on the messy long tail of real-world driving.
• Optimize for Real-Time:
  • Partner with embedded teams to ensure models meet strict constraints (latency memory throughput) and integrate cleanly via stable interfaces.

What We Look For:

• MSc in Robotics Computer Vision Electrical Engineering or a related field
• Strong mathematical foundation in linear algebra probability estimation theory optimization and 3D geometry
• Strong understanding of sensor fusion localization and state estimation methods including Kalman filtering and factor graph optimization
• Strong software engineering skills in Python and C
• Experience designing implementing and debugging complex robotics system
• Ability to lead architectural discussions articulate tradeoffs quantify technical risks and define realistic development milestones

Bonus Points:

• PhD in Robotics Computer Vision Electrical Engineering or a related field
• Experience designing and deploying SLAM localization odometry or calibration algorithms on real robotics platforms in challenging environments
• Experience with tightly coupled fusion of visual inertial and radar data
• Practical and theoretical understanding of sensor noise synchronization observability degeneracy and failure modes

What We Offer:

• Opportunity to make an impact at a young venture-backed company in an emerging market
• Competitive salary ranging from 82000 to 115000 annually depending on experience and equity
• Hybrid work model: in office 3 days per week (Tuesday Wednesday Thursday) the rest work from wherever!
• Modern Workspace: Fully equipped modern office on the beautiful lake Constance in the Alpine foothills
• Daily lunch supported by a fixed amount for in-office days to be used freely at your discretion and a stocked fridge in the office
• Egym Wellpass

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.