Backed by Y Combinator.
About the role
We’re looking for a recent graduate to join us for a 6-month intern-to-hire role working across our robotics stack: perception, controls, simulation, and robot applications such as asset tracking and site monitoring. The common thread is measurement. You’ll design experiments and build the tools that tell us whether our systems work, how well, and why, then share what you find with the ML and control engineers who act on it. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Recent graduate (Bachelor’s or Master’s degree) in engineering, physics, mathematics, or a related technical field
- Proficiency in Python, experience with C++ is a plus
- Familiarity with Linux environments
- Experience using agentic coding tools (e.g., Claude Code, Cursor, Codex)
- Experience designing and conducting experiments from a scientific perspective and applying statistical analysis to extract insights from noisy, real-world data
- Strong written and verbal communication skills, including the ability to clearly articulate technical results to both technical and non-technical stakeholders
More about this role
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 real world.
Although...
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