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Electrical Engineer

Microagi

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  1. Why do you want to join Microagi?
  2. What is your experience with C++? Tell me one thing you learned the hard way.
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  4. What do you do when a production issue happens on your code?
  5. Walk me through a system you built. How was it designed, and what would you change now?

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Accelerating embodied AGI. The next ten years of AI will not be won in software. They will be won in the physical world: in factories, hospitals, kitchens, fields, and homes. The companies that own that data will own the century. MicroAGI is building it. We are a data research and deployment lab. Atlas captures the manual work inside Europe’s industrial champions, trains foundation models on it, and deploys the right robot onto the floor, with no teleoperation and no interruption to the line. Shift records how physical work actually happens and turns it into training-ready data. We were founded by former Formula 1 engineers from Red Bull Racing and Mercedes, together with a researcher from the Alan Turing Institute. Our $55M seed round, the largest in German history, was led by Hummingbird with Northzone, LocalGlobe, Village Global, and redalpine. We are based in Munich, with our research centre in Zürich and teams in London, New York, and Istanbul. We are now building the engineering and research teams that will take Atlas into new industries. Our models learn from data captured in the physical world, by hardware we design and build ourselves. As Electrical Engineer, you will own that hardware end to end, from sensor choice and PCB to firmware, so that the data reaching our ML team is clean, synchronized, and trustworthy. 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. Who Will Thrive at MicroAGI Everyone we hire is assessed on the same four traits: Mission and vision: you care about what we are building and why it matters, and your past choices show it. Intensity: you work at a pace that matches the size of the opportunity, and you sustain it. Entrepreneurial: you start things nobody asked for, and you finish them. Raw IQ: you learn fast, reason from first principles, and get sharper when the problem changes. This is for you if: You would rather own a problem end to end than wait for a spec. You use AI every day, and you can tell a correct answer from a plausible one. You want to work in person, in the office, with people who are very good at what they do. This is not for you if: You are looking for a predictable 9-to-5. You would forward output you cannot explain. "That’s not my job" feels like a reasonable answer. How We Hire We read every application and reply within five working days. Talent Screen (30 min): a first conversation, both ways. Technical or Functional Interview (60 min): how you think when the problem changes. Your Work (60 min): bring something you are proud of and walk us through it. Leadership (30 min): a conversation with our CEO. Coworking Day (engineering and research roles): a day building with the team on a real problem. Then a decision, usually within a few days. 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. Equal Opportunity MicroAGI welcomes applications from everyone. We assess candidates on their work and potential, regardless of ethnic origin, gender, religion or belief, disability, age, or sexual identity. Find more English Speaking Jobs in Switzerland on Arbeitnow

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Listed on arbeitnow · posted 2026-10-13. ApplySarthi collects openings and links to application pages; the role is advertised by Microagi, not by us.