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Robotics & Machine Learning Engineer

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Onsite

Robotics & Machine Learning Engineer

Faction Imaging Inc

Robotics & Machine Learning Engineer

Skills

PythonMachine LearningAI

3 months ago

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Important information


Contract type:

Permanent

Location:

New York, NY, USA

Work mode:

Onsite

Published on:

7 August 2026

What they need


Faction Imaging is building the intelligence that allows robots to autonomously interact with the human body to collect rich medical data.

We're looking for a resourceful and hard-working Robotics Machine Learning Engineer to test, evaluate and improve machine learning systems on real robotic platforms. You'll work closely with experienced engineers to design experiments, benchmark new approaches, and improve the performance and reliability of autonomous systems.

What We're Looking For

  • Experience operating and testing autonomous robotic systems in a lab environment
  • Experience collecting and analyzing data with statistical methods
  • Experience with common robotics sensing hardware: RGB cameras, depth cameras, force sensors, tracking systems, etc.
  • Experience with real time publish/subscribe communication protocols (e.g. ROS 2)
  • Experience with multi-threading and asynchronous python
  • Experience with modern machine learning methods for robotic control: behavior cloning, reinforcement learning, or related learning methods
  • Extensive experience with the python programming language and related machine learning libraries
  • Experience in autonomous navigation is a major plus
  • Familiarity with real time robotic control systems is a plus

Job Details

Faction is located in downtown Manhattan, New York City. This is an in-person job requiring significant percentage of your time on-site.

Why Faction

Faction is tackling a frontier problem in Physical AI: creating robots that can safely perceive and directly interact with the human body. You'll work alongside experienced engineers on real robotic systems and contribute directly to the mission of expanding access to high-quality medical care.

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