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 Head of Hardware, you own that hardware end to end: electrical, firmware, and the mechanical integration that holds it together, from the first schematic to devices running on factory floors.

You lead the team that builds it. Today that is about six engineers on robotics, three on EMG sensing, and three on camera systems, plus contractors, and it will grow quickly. Our Electrical Engineer and Embedded Engineer roles report to you. You set the architecture they build against, and you still build alongside them.

This is a founder-shaped role, not a management seat. We are looking for someone who has carried a product from a blank page to customers with real skin in the game, wants to build both the thing and the team that builds it, and would rather design than review. If that sounds like you, you will want to do it again at the earliest stage.

What You Will Do

Own the hardware roadmap for Shift and Atlas data capture: wearables, sensor rigs, camera systems, and prototype robots. What we build, in what order, and why.
Set the system architecture across electrical, firmware, and mechanical: sensors, compute, power, wireless, and enclosures. Make the trade-offs, and make them stick when disciplines disagree.
Stay on the bench: schematics, layout reviews, board bring-up, and a scope in your hands when the team is stuck. On the days it matters, you are the best electrical engineer in the room.
Lead and grow the team: hire, set the bar, run design reviews, and give engineers ownership of whole subsystems rather than tickets.
Guarantee data quality end to end: EMG and EEG front ends, camera pipelines, IMUs, and synchronization across many devices, so that what reaches the ML team is clean, time-aligned, and trustworthy.
Take designs from prototype to small-batch production: DFM, component and EMS vendors, test fixtures, certification, and field reliability.
Work shoulder to shoulder with ML and deployment. Your hardware decides what the training data looks like, and you will be on the floor where it is captured.
Run contractors and partners without losing ownership of the result.

Requirements

You have taken at least one product from zero to shipped, with significant ownership of the outcome: as a co-founder, CTO, first hardware hire, or the lead who owned the whole device. Not one subsystem, not one phase. Ideally a wearable, at a tier-one hardware company known for shipping at scale.
Electrical engineering is your home discipline. You have designed boards that shipped, across mixed-signal, power, wireless, and high-speed digital, and you can still do it today.
You think in systems. You understand how an electrode choice, an enclosure tolerance, and an ADC sample rate interact, and you can hold the mechanical and firmware conversations as a peer, not a customer.
You have led engineers: hired them, grown them, and kept a team shipping through 0-to-1 ambiguity. Typical 6+ years in hardware, but we care more about what you shipped than how long it took.
A strong understanding of how hardware decisions affect data quality. You know that a great model on a noisy signal still loses to a decent model on a clean one, and you design accordingly.
Experience taking hardware to small-batch production: DFM, vendor and EMS management, test, and certification.
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. A 0-to-1 hardware program takes the hours it takes, in person and at pace, and you have chosen that before.
Discreet: you handle confidential hardware roadmaps and customer data with care.

Nice to Have

Wearables, smartwatches, drones, robotics, AR/VR, or defense wearables on your résumé.
Camera systems: sensor selection, MIPI and ISP pipelines, and multi-camera synchronization.
Low-power and battery design, BLE or Wi‑Fi, and antenna integration in small enclosures.
Enough mechanical fluency (CAD, tolerances, and materials) to challenge the mechanical team’s choices and be right some of the time.
Prior founder or founding‑engineer experience, including the parts that went wrong.
Open‑source hardware or firmware contributions.

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.

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