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Embedded Software Performance Engineer
- Berkeley, California, United States
- Berkeley, California, United States
Über
Zendar pioneered RF perception that delivers a vision‑like, semantically segmented understanding of the environment—running on embedded automotive systems using only radar data. This RF perception forms the backbone of Zendar’s 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, Zendar’s models combine vision’s high angular resolution with RF’s 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.
At Zendar, you’ll work at the cutting edge of autonomous mobility and robotics—advancing foundation models that will power the next generation of physical AI systems. You’ll 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 résumé is reviewed by a real person.
See a demo of Zendar’s foundational RF perception
Your Role: Zendar’s Semantic Spectrum perception technology extracts a rich scene understanding from radar sensing, augmented by additional sensors such as IMU and cameras. In addition, Zendar is building an actuation stack on top of its perception outputs. All of these capabilities must run reliably, efficiently, and with deterministic timing on ruggedized embedded platforms suitable for field deployment in the field.
We are seeking experienced software engineers to implement and optimize a high‑performance pipeline capable of handling these intensive workloads, leveraging the accelerators available in modern heterogeneous embedded computing platforms. This position is ideal for engineers who are passionate about pushing the limits of modern computer hardware to achieve higher performance, and who are interested in bridging the gap between machine learning research and deployment of AI models on the edge.
It is an exciting opportunity to tackle real‑world challenges in bringing algorithms developed in the lab to vehicles operating in diverse physical environments.
What you’ll do: In this role, you will work closely with our researchers to explore the trade‑offs between algorithm output quality and its compute efficiency, while creating performance optimized embedded implementations runnable on our production hardware. You will also collaborate with product teams to tackle performance issues encountered in the deployment of our software. To have a thorough understanding of the heterogeneous computing platform we target, you are expected to devise methodologies and microbenchmarks to exercise relevant processing blocks in the system. The knowledge acquired would be incorporated into the evolution of our software system architecture.
What We Look For:
Proficiency with modern C++ (we use C++ 17) and python
Experience programming multiprocess/multithreaded applications in production environment
Experience profiling and analyzing the performance of C++/python applications
Experience in optimizing performance for compute intensive workloads on modern computer systems
Experience developing for embedded Linux or POSIX systems
Familiarity with professional software development tools, such as source control (git), unit testing, and profiling
Strong communication and cross‑functional collaboration skills
Bonus Points:
Experience with developing mission critical software (e.g. aviation or autonomous vehicles)
Experience developing software that runs on an RTOS
Experience with radar, lidar, cameras, GPS/IMU, or other automotive sensors
Experience mentoring team members on software development and best practices
Familiarity with CUDA/OpenCL
Experience deploying machine learning models in embedded systems
What We Have To Offer:
Opportunity to make an impact at a young, venture‑backed company in an emerging market
Competitive salary from $140‑200k depending on experience, benefits and equity
Daily catered lunch and a stocked fridge (when working out of the Berkeley, CA office)
Zendar is an equal opportunity employer.
Zendar participates in E-Verify.
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Sprachkenntnisse
- English
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