Machine learning engineer Jobs in Lugano

We're a VC-funded, Swiss-based startup looking for a senior backend developer with experience in Next, React and Typescript.

Generative AI will transform fashion content creation, but managing (searching, culling, selecting) amoong tens of thousands of images is a complicated. Editing them in the browser using AI (hence probabilistic) algorithm in a userfriendly way is the second big challenge.

We want to build a product that our business user love to use.

The role

You will own meaningful backend domains end-to-end and add real throughput where the team currently bottlenecks. The focus here is backend depth — that's the bar — alongside a deliberate, bounded slice of platform and security work. Full-stack engineers who clear the backend bar are equally welcome: we care about what you can carry on the backend side, not about whether you also work on the frontend.

The most interesting backend problem at Sartiq today isn't a feature backlog — it's an architecture one. We're pushing past tens of thousands of high-fidelity generations a day, customer integrations are deepening per brand, and the surface between our product, our AI generation layer, and the data we accumulate from it is becoming the part of the system that earns the company most of its leverage. That's the work.

What you'll own

Backend product engineering (~80%)

• Core product backend services. Design and build the services behind the main app: APIs, data models, business logic, the contracts that define how the product actually behaves to customers.
• Customer integrations. Each major customer ends up with their own backbone behind the scenes — export pipelines, transport adapters, naming conventions, automation. You'll own end-to-end pieces of this and help shape it into something more repeatable as the customer base grows.
• AI generation pipeline — as a backend architecture problem. Clean service boundaries, robust job lifecycle and state, sharp retry/failure semantics, the right contracts between the product and the generation layer. As we push past tens of thousands of generations a day, this is the part that has to keep getting sharper. This isn't an infra problem dressed up — it's real backend architecture work.
• Data engineering as it grows. Production data flows, usage analytics, the internal data platform — a surface starting to take real shape. You'll contribute to (and help define) what it becomes.

Platform & security (~20%)

• DevOps/SRE backup (~10%) — be the second pair of hands in the infrastructure rotation: CI/CD, deployments, observability, fallback coverage during PTO or incident peaks. A deliberate, bounded slice — enough that we stop being a one-person operation here.
• Security (~10%) — own targeted security projects as part of normal work: auth flows, secret management, dependency hygiene, internal tooling. Real pieces of meaningful work, not vague oversight.

What success looks like in 6 months

• You own at least one backend domain that the team routes work to you for
• A customer integration or core service you led is in production carrying real load
• One concrete security project — auth, secrets, dependencies, or similar — is meaningfully better than when you started, not just tracked
• You've taken real load off the infrastructure rotation

Tasks

1. Mid-to-senior backend engineering experience. Most likely you have around 3–5+ years of professional experience, but the real bar is ownership, judgment, and shipping quality. Python is our primary stack (FastAPI, SQLAlchemy, async) and you'll write it most days. Real depth in another modern backend (Go, Rust, Node.js, Java, …) is a credible path here too, as long as you've shipped something in Python and pick up new stacks fast.
2. Strong SQL — schema design, complex queries, migrations and indexing under real data
3. Backend architecture instincts — you can reason about service boundaries, contracts, queues, state, failure modes, observability — not just CRUD
4. Solid security fundamentals — auth flows, OWASP-class vulnerabilities, secure-by-default habits, secret management
5. Light but real DevOps fundamentals — Docker, Linux, CI/CD
6. A track record of shipping production features fast without leaving a mess
7. You use AI coding agents fluently and critically — they speed you up, but you still review output, understand failure modes, write tests, and ship production-quality code
8. Fluent written and spoken English

Bonus

• Cloud experience on any major platform (AWS, GCP, Azure, …) — we deploy with Terraform and aren't tied to one cloud
• Task queues (Celery/Redis), async pipelines, Postgres operational concerns under load
• ML/AI service integrations (Vertex AI, OpenAI, Fal, Replicate, …)
• Data engineering experience — pipelines, analytics, internal data tooling
• Security background — certifications, CTFs, homelab, prior security-focused work
• You genuinely enjoy building with technology beyond assigned tickets — personal projects, automations, experiments, tools for yourself or others, OSS, software-and-hardware tinkering, or past side projects you still care about
• You use AI for more than just code — agentic harnesses, automated personal pipelines, custom tooling for your own life
• Italian — the team speaks Italian day-to-day, so it's a real plus; English alone is fully sufficient

Requirements

This role is probably not for you if…

• You want a pure feature role with zero architecture, infrastructure, or security exposure
• "Backend" to you means CRUD over a single service — the scale, integration, and architecture work here will bore you if you don't enjoy that side
• You're frontend-first and see backend as the part you tolerate
• Writing software is only a way to earn a salary for you, and you have little curiosity for technology outside assigned work

Benefits

1. Autonomy & Impact: You won't be a ticket-taker. You'll have the agency to own the backend developement lifecycle for core features, from hypothesis to production, and see your work ship.
2. Competitive Compensation & Equity: We offer a top-tier salary and a meaningful stock option plan. We want you to have a real stake in what you're building.
3. A Lean, Expert Team: You'll work directly with the founders in a fast-paced environment, free from corporate bureaucracy.
4. Hybrid Work Model: We think that being in the same room often boosts productivity, so we want you in the office at least 2 days per week. But we have no schedule. You decide when to work to maximise your productivity.

If you're an engineer who is obsessed with the generative space and wants to apply your skills to hard problems with real-world impact, we would love to hear from you.

Our interview process is straightforward:
1. You share your github + portfolio + CV

2. Technical challenge
3. A chat with the founders