Robotics Vision Engineer: Grounding Language & Perception

ndimensions labs

Boston (MA)

On-site

USD 130,000 - 180,000

Full time

2 days ago
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Job summary

Ndimensions is building the infrastructure for next-generation robotics AI systems, and seeks a Robotics Perception Engineer to own the perception layer. The role sits between AI and navigation teams, tackling vision problems to verify object grounding, language grounding to pixels, and real-time on-robot inference on embedded GPUs.

It is a hands-on role on real hardware in real homes. You will work with Python and C++ in ROS2, calibrate cameras, build semantic maps, and support ground-truth

Qualifications

  • Strong background in computer vision for robotics.
  • Experience grounding language to pixels.
  • Experience with depth sensing and 3D scene representations.
  • Experience deploying detection/segmentation models on embedded GPUs.

Responsibilities

  • Bridge language and pixels to verify the grasped object matches the instruction.
  • Ground language in the scene to produce a pick target or navigation goal.
  • Build a persistent, object-level map that can be queried by language.
  • Classify dynamic vs static elements to indicate trustworthy map regions.
  • Evaluate and deploy perception models with real-time latency constraints on embedded GPUs.
  • Calibrate cameras and manage depth/localization accuracy.

Skills

Robotics CV
Vision-language grounding
Python
C++
ROS2
On-robot experimentation

Education

Master’s or PhD in Computer Vision / Robotics

Tools

ROS2
OpenCV
CUDA
PCL

Job description

Ndimensions is building the infrastructure for next-generation robotics AI systems, and seeks a Robotics Perception Engineer to own the perception layer. The role sits between AI and navigation teams, tackling vision problems to verify object grounding, language grounding to pixels, and real-time on-robot inference on embedded GPUs.

It is a hands-on role on real hardware in real homes. You will work with Python and C++ in ROS2, calibrate cameras, build semantic maps, and support ground-truth

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