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microagi

Robotics deployment platform for site-specific AI

Electrical Engineer

Hardware Systems IntegrationConfirmed live in the last 24 hours
Full-timeZürich, Switzerland

About the Job

Requirements

  • Have up to five years of experience building production-grade hardware or Internet of Things systems.
  • Have strong embedded-software skills in C/C++, real-time operating systems, and microcontrollers such as STM32, ESP32, or NXP.
  • Have experience integrating sensors such as inertial measurement units, cameras, depth sensors, or force sensors.
  • Understand how hardware decisions affect data quality, especially for electromyography and electroencephalography sensing, including electrode placement, sample rate, filtering, noise floor, and motion artifacts.
  • Be comfortable with printed circuit board design and hardware debugging using tools such as logic analyzers and oscilloscopes, with firmware experience.
  • Be genuinely curious about machine learning, have read papers, trained at least one model end to end, and understand the importance of dataset quality relative to model architecture.
  • Be comfortable working with high agency in ambiguous, early-stage situations.
  • Handle confidential hardware roadmaps and customer data discreetly.
  • Be fluent in English.

Responsibilities

  • Design, build, and integrate hardware for capturing model-training data, including sensors, motion-capture rigs, custom Internet of Things setups, and prototype robots.
  • Own the firmware and embedded-software layer, including real-time data collection, multi-sensor synchronization, calibration, and time-stamping.
  • Specify and select sensors and computing hardware for new projects, balancing physical constraints against downstream machine-learning needs.
  • Work closely with machine-learning engineers to deliver clean training data through the hardware.
  • Rapidly prototype bench builds, custom rigs, and working devices.

Desired Qualifications

  • German language ability.
  • A background in robotics, motion capture, or wearable devices.
  • Experience with real-time or hard-deadline systems, such as audio, video synchronization, or robotic control loops.
  • Familiarity with machine-learning training pipelines and the ability to read a training script.
  • Open-source firmware or hardware contributions.
  • Experience scaling from prototype to small-batch production, including design for manufacturability, vendor management, and certification.

About the Company

microagi

Robotics deployment platform for site-specific AI

MicroAGI helps factories deploy robots that learn from their own data. Its Atlas platform fine-tunes AI models on a factory’s data so robots perform reliably on real production tasks. Atlas sits between a manufacturer’s systems and AI models and works with any hardware or model vendors, avoiding vendor lock-in. The company aims to scale Atlas across major European manufacturers to reduce skilled-labor gaps and energy costs by making robotics more site-specific and adaptable.

Company size
51-200
Company stage
Seed
Total funding
$55M
Headquarters
Munich, Germany
Founded
2025

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