Publiée 29 juillet 2026
Sensor Fusion and Localization Engineer
Zendar
Paris, Île-de-France 75000, France
CDI
Zendar is looking for a Sensor Fusion & Localization Engineer to join our Paris 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 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 rear world.
Although AI is central to what we build, our hiring process is intentionally human: every résumé is reviewed by a real person.
Your Role:
As a Sensor Fusion & Localization Engineer in Paris, you will design and implement the state estimation framework behind Zendar's 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:
What You'll Do:
What We Look For:
Bonus Points:
What We Offer:
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.
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 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 rear world.
Although AI is central to what we build, our hiring process is intentionally human: every résumé is reviewed by a real person.
Your Role:
As a Sensor Fusion & Localization Engineer in Paris, you will design and implement the state estimation framework behind Zendar's 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 You'll 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 €75,000 to €90,000 annually depending on experience and equity
- Hybrid work model: in office 3 days per week (Monday, Tuesday, Thursday), the rest... work from wherever!
- Modern Workspace: Fully equipped, modern office in the heart of Paris
- Transportation/Commute: Commuter benefits (partial reimbursement for public transport, where applicable)
- Subsidized meal vouchers (tickets restaurant)
- Wellness Pass (ex Gymlib)
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.