Location: Hybrid in New York or Philadelphia
Salary: $160K to $190K
Work Policy: Hybrid. Must be based in NY or Philly metro areas
Visa Sponsorship: Available. We can handle most visas
We’re hiring for an engineer who understands perception and systems. If you’ve built SLAM systems that actually run on moving robots and you’ve had to deal with sensor quirks, calibration drift, and noisy environments you’ll thrive here
This isn’t academic. This isn’t a vision only role. We want someone who’s owned the pipeline from sensor to map, who stays close to the hardware, and who ships code that survives in the real world
What You’ll Be Doing
• Building and deploying SLAM systems using ground based LiDAR
• Integrating and tuning sensors directly on vehicles, drones, or mobile robots
• Working on perception systems that map environments at scale, beyond just object or room detection
• Leading sensor calibration workflows, both manual and automated
• Fusing multiple sensor types into a coherent real time perception pipeline
Must Haves
• 4 plus years working on robotics perception and mapping problems
• Deep SLAM experience using LiDAR in real environments
• Proficiency in both C++ and Python
• Strong understanding of intrinsic and extrinsic calibration, including data driven methods
• Experience with multimodal sensor fusion and ultra wide angle cameras
• Hands on mindset. You’ve worked directly with real hardware, not just datasets
What You Bring
• Curiosity, adaptability, and a mission first mindset
• Comfort with fast moving teams and real world constraints
• A practical obsession with making perception systems reliable in dynamic environments
Not a Fit If…
• Your idea of perception stops at object recognition
• You’ve only worked in one narrow part of a large perception stack
• You don’t care how the full system behaves as long as your algorithm runs
This role is about building tough, production grade robotics perception systems. You’ll be part of a team that cares about performance in the field, not theoretical benchmarks
Apply now if you want to solve hard perception problems with full system context and real world feedback