Autonomous Drone Vision Engineer

Rownd; North Carolina; Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Equity

Hybrid-remote work

Competitive salary

Job summary

Rownd seeks an Edge Vision Engineer to design, build, and deploy the visual intelligence powering our autonomous drones and edge assets. You will own the entire vision pipeline, from camera selection to model deployment on edge devices, optimizing for speed and memory on constrained hardware.

You will test, validate, and iterate across hardware and software stacks in a fast‑paced startup environment. In this role you will work across hardware and software, integrating CV stacks with CUDA‑enabled

Qualifications

• US Citizenship: eligible to obtain and maintain U.S. Security Clearance.
• Edge & NPU Expertise: deploy CV models to hardware with quantization and memory constraints.
• Core Tech Stack: PyTorch/TensorFlow, OpenCV, TensorRT, CUDA, C++, Python.
• Just Do It Mentality: prototype, test, break, and fix in ambiguous environments.
• Location & Travel: prefer non-traditional tech hubs; travel 4–5 weeks per year.

Responsibilities

• Edge Model Design: select cameras and processors; design the vision stack.
• Deploy fast, small models on edge devices with optimization for latency and power.
• Cross‑platform deployment to CUDA devices and NPUs; ensure robust evaluation.
• Integrate CV pipelines with drone navigation and control systems.
• Collaborate across hardware, software, and field teams; own end-to-end delivery.

Skills

US Citizenship

Edge & NPU Expertise

Just Do It Mindset

Location Flexibility

Travel Flexibility

Tools

PyTorch/TensorFlow

OpenCV

TensorRT

CUDA

C++

Python

Job description

Rownd seeks an Edge Vision Engineer to design, build, and deploy the visual intelligence powering our autonomous drones and edge assets. You will own the entire vision pipeline, from camera selection to model deployment on edge devices, optimizing for speed and memory on constrained hardware.

You will test, validate, and iterate across hardware and software stacks in a fast‑paced startup environment. In this role you will work across hardware and software, integrating CV stacks with CUDA‑enabled