microagi · AI infrastructure
Electrical Engineer
- Zurich (On‑site)
- Full-time
Still open on microagi's site · checked just now
- Posted
What you'll do
As written by microagi · Read the original
What You Will Do
Design, build, and integrate the hardware that captures the data our models learn from: sensors, motion-capture rigs, custom IoT setups, and prototype robots.
Own the firmware and embedded-software layer: real-time data collection, multi-sensor sync, calibration, and time-stamping.
Spec and select sensors and compute for new hardware projects, balancing physical constraints against downstream ML needs.
Work shoulder to shoulder with ML engineers. Your hardware delivers their training data, and bad sensor choices haunt them for months.
Prototype fast: bench builds, custom rigs, breadboard to working device in days, not quarters.
Requirements
Up to 5 years building production-grade hardware or IoT systems.
Strong embedded-software skills: C/C++, RTOS, and microcontrollers (STM32, ESP32, NXP, or similar).
Experience integrating sensors: IMUs, cameras, depth sensors, force sensors, or similar.
A strong understanding of how hardware decisions affect data quality, especially for EMG/EEG sensing: electrode placement, sample rate, filtering, noise floor, and motion artifacts. You know that a great model on a noisy signal still loses to a decent model on a clean one, and you design accordingly.
Comfortable with PCB design and hardware debugging (logic analyzer, oscilloscope), with at least one foot in firmware.
Genuinely curious about ML: you read papers, you have trained at least one model end to end, and you understand that dataset quality beats model architecture choice.
High agency: you don't wait to be told what to do. You are comfortable in 0-to-1 ambiguity, where the spec is "figure out what the spec should be".
Discreet: you handle confidential hardware roadmaps and customer data with care.
Fluent in English. German is a plus.
Nice to Have
A background in robotics, motion capture, or wearable devices.
Experience with real-time or hard-deadline systems: audio, video sync, or robotic control loops.
Familiarity with ML training pipelines. Even if you don't run them, you can read a training script.
Open-source firmware or hardware contributions.
Experience scaling from prototype to small-batch production: DFM, vendor management, and certification.
Skills
Stack
- C++
- C
Working languages
English
Salary & benefits
Pay Transparency
Compensation includes base salary and equity. The salary range for this role is shown on this posting.
What We Offer
Agency: real ownership from day one, and decisions that actually matter.
Freedom: to choose how you solve the problem, without layers of approval.
A seat on a rocketship: one of Europe’s fastest-growing deep-tech companies, at the earliest stage.
Free food and drinks in the office.
Company
Last checked . The details above were extracted automatically; the employer's original posting is the authority.
