What we do
Flycatcher builds unsupervised visual anomaly detection for industrial inspection. Our system learns what normal looks like from a handful images, then flags everything else in milliseconds, on commodity hardware. No pre-labelled defect data.
The technology comes out of 6+ years of research at IDSIA, a Swiss AI research institute affiliated with USI and SUPSI. We are supported by NVIDIA Inception and funded by Venture Kick, one of Switzerland's main early-stage startup funders, and we are a finalist at MassChallenge, which TIME and Statista ranked the number two accelerator in the United States in August 2026.
That technology works, and the pipeline is now growing faster than our current team can serve it. What we need is more engineering depth, so we can push harder on delivery instead of choosing which customers to say yes to. That is the turn you would be joining at.
Who you work with
- Dario Mantegazza (CEO, co-founder): owns the research direction and the anomaly detection core. PhD, 6+ years at IDSIA.
- Arianna Marsilio (CPO, co-founder): owns product. Second-time founder, 10+ years in UK startups from early stage to hyper-growth.
- External technical support: an ex-Amazon scientist and an EPFL-trained AI engineer, who you will work alongside.
Tasks
What you own
You are the first senior technical hire, and you are taking over a codebase rather than joining one.
Engineering architecture and delivery. Production systems, from the edge node to the customer dashboard. The training and inference API. Cloud infrastructure and its cost curve. Automation of deployment. Technical hiring. The call on what we build and what we buy.
What you will have achieved
Customers are running our system in paid pilots today. Turning those into production deployments that run every day without us is the work ahead, and leading it is the core of this job. Expect your hands dirty, in the code and in front of customers, for the first few months.
First 90 days
- You have taken the codebase over without a single client delivery slipping.
- You have been on site with customers, delivered our solution to them yourself, and can describe the value we provide in their words rather than ours.
- You have told us where the system will break first, how big that problem is, and what the fix could look like.
By month 6
- You have shipped the API alpha to a partner integrator.
- You have turned a POC into a production deployment that runs unattended and that a customer now relies on. Nobody here has done that before you.
- You have made deployment repeatable and written it down, so the second one costs a fraction of the first, and you have measured configuration hours per facility so we know what we are improving against.
- You have a hiring plan ready to run the moment we grow: roles scoped, bar set, candidates already warm.
By month 12
- You and your team are running five POCs and the first live facilities without a founder in the delivery loop, and you have opened our first manufacturing deployments.
- You oversaw the launch of the Automation Engine alpha working internally, measured against the baseline you set in the first six months.
- Your first three to five engineers hired and productive, with a real on-call and incident process.
By month 24
- You took the Automation Engine and the plug-and-play product in beta.
- You have put API V1 in public hands: authentication, key management, rate limiting, and a support process you built on purpose.
- You have around fifteen facilities running, and manufacturing deployments that no longer need a bespoke rebuild.
- You have driven infrastructure cost per facility low enough that our licence pricing holds its margin at scale.
- You have built an engineering team that hires, ships and recovers from incidents without a founder in the room.
The stack: loose on tools, tight on outcomes
Today we are Python-native; our proprietary models are written using PyTorch, the services are FastAPI, currently we use Azure for cloud: blob storage for models, SQL for customer data, GPU compute for inference.
What sits at the customer end is often not our choice. One site will be a Jetson we install, the next a server in their rack, the next something in their cloud. You will find out on arrival.
That is what we run, not what you must keep. Part of what we are hiring is your judgement about what should change.
FFmpeg, OpenCV and the rest are the barebone of the vision stack.
Requirements
What we think this needs
The technical bar below is high, but it is not what makes this role hard to fill. Plenty of people clear it. The rarer part is the first three.
- You can carry the company, not only the code. You can sit with a terminal operator, understand what their day costs them, and turn that into a deployment they will pay for. You can represent us to a partner or an investor without a founder translating.
- You build the team, not only the system. You will hire the people who come after you, set the bar they are measured against. You know what a rushed early hire costs, and you would rather wait for the right one.
- Judgement about what matters. You set the technical agenda rather than receive it, and you are as clear about what we should not build as what we should.
- A deliverer who has seen scale. You ship things that work now, and you have been somewhere that scaled, so you know which shortcuts you will pay for later. What you write in year one does not have to be the code that carries us to hundreds of facilities. It has to be the code that gets a customer live.
- Production ML, not research ML. You have taken models from a notebook to systems other people depend on, and you have lived with them afterwards.
- Real depth in computer vision and cameras. Enough to make architecture calls confidently, and challenge Dario usefully.
- Hands on the hardware. You do not need to be an embedded or electrical engineer, but you are familiar enough to get a box running without waiting for one. If you have squeezed models onto small hardware before, that helps.
- In front of customers. You are comfortable on a customer site, in their terms, without a founder in the room.
- Full-stack pragmatism. You can ship functional user-facing code end to end.
- Startup DNA. Comfortable with pace, ambiguity, and a roadmap that changes when a customer teaches us something.
- English fluent. Italian and German are a plus.
Signals this is NOT for you
- You want to lead a team more than you want to build. For the first few months, you are the team.
- You want a roadmap to execute. Here you help write it, with two founders who want your opinion as much as your code.
- Remote for you means fully asynchronous and no travel. A real part of this job happens at customer sites or in front of a physical product in a lab.
Benefits
How we work
Where you work from is your call as long as the timezone is compatible (CET ±2). If you’d like our office in Lugano is ready to welcome you.
During onboarding we will ask you to be in Lugano for a few weeks. It is there to accelerate getting to know each other, get the handover done properly, and build a foundation before you are working at a distance. After that we meet in person regularly, roughly once or twice a month early on, less often as the processes settle.
Remote here means asynchronous by default and written by default. It does not mean isolated, and it does not mean stationary: part of this job happens in front of customers, at their gates and on their production lines, looking at the actual containers and the actual machines. Expect to travel often.
Compensation
- Base: CHF 80,000 to 130,000, depending on location and seniority + Equity.
- Full time.
This is the starting point, not the shape of the thing. Scope, equity and salary all move as the company does, and we would rather talk about that in the first conversation than the last.
What else we offer
- Ownership. Direct control of Flycatcher's technical direction, architecture and product engineering.
- Velocity. Decisions in hours, your code in production in weeks. No silos, no hierarchy.
- A culture of builders. Ownership, speed and intellectual honesty. We share context openly and solve problems together.
- Elite ecosystem. NVIDIA Inception, MassChallenge, and active research partnerships with IDSIA, USI and SUPSI.
- Growth beyond the code. Customer negotiations, investor conversations and hiring decisions, from day one. How far that goes is set by how fast we grow, not by a ladder someone wrote in advance.
If you're passionate about AI, eager to directly contribute to the growth of an ambitious startup, and driven by impactful work in the transportation and logistics space, apply now and let's discuss your future at Flycatcher!