Senior Software Engineer

trg.; Zug; Hybrid; CHF 110,000 - 150,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

trg. in Zug, Switzerland, is seeking a Senior Software Engineer (Backend/ML Systems) to own and ship production-ready backend systems.

The role combines Python-based API work with ML model deployment in a fast-paced setting, with 4 days onsite and 1 remote, under a startup-like culture backed by a global organisation. You will work across the stack when needed, with responsibilities spanning design, deployment, monitoring, and scaling of ML-enabled services.

Qualifications

• Strong Python engineering background with hands-on framework experience (FastAPI/Flask/Django).
• Proven track record deploying and monitoring ML models in production.
• Solid Docker and containerisation experience; CI/CD pipelines with GitHub Actions.

Responsibilities

• Own backend systems end-to-end, shipping production-grade software in a fast-moving environment.

Skills

Python

Backend development

ML deployment

Lean/startup experience

Tools

Docker

GitHub Actions

FastAPI

Flask

Django

Job description

Senior Software Engineer (Backend/ML Systems)

Zug, Switzerland (4 days onsite, 1 remote)

No sponsorship available

2-stage interview process

Stack: Python, FastAPI/Flask/Django, Docker, GitHub Actions, ML deployment

Salary: CHF 110k - 150k+ (plus bonus)

We're working with a fast-growing AI Engineering team based in London on a Senior Software Engineer hire. The team has a genuine startup culture, small, focused, high ownership, backed by the scale and resources of a major global organisation. They build AI-driven technology that has measurable real-world impact on how large-scale infrastructure is designed and built.

This is a hands-on backend role for someone who's comfortable owning systems end to end, moving across the stack when needed, and shipping production-grade software in a fast-moving environment.

What you'll need

• Strong Python engineering background with hands-on experience in FastAPI, Flask, or Django
• Proven track record of deploying and monitoring ML models in production environments
• Solid Docker and containerisation experience
• CI/CD pipeline experience, GitHub Actions specifically
• A background in startups or scaleups where you've had real ownership and worked in lean teams
• Someone who can move across the stack and pick things up quickly rather than staying in a narrow lane

Nice to have

• Observability tooling such as Prometheus, Grafana, or ELK
• Infrastructure as Code (Terraform)
• Azure cloud experience
• GPU/CPU workload optimisation

The details

Location: Zug, Switzerland (4 days in office, 1 remote).