Machine Learning Engineer

Try&Hire; Genf; On-site; CHF 120,000 - 180,000; Full time

Job summary

Try&Hire in Switzerland (Genf) seeks an experienced ML engineer to design and deploy scalable ML systems for real-time threat detection and anti-abuse protection. You will work on agentic AI systems, model development tooling, and explainability while collaborating with security analysts and frontend/backend engineers.

The role requires hands-on ML production experience, proficiency in Python, and a strong foundation in probability and experimental design.

Qualifications

• Degree in Computer Science or a related quantitative field.
• 2+ years hands-on experience building and running ML systems.
• Production-level ML expertise with models at real-world scale.
• Hands-on experience with LLMs in agentic environments.
• Strong proficiency in Python and backend/server fundamentals.
• Deep understanding of probability, hypothesis testing and experimental design.

Responsibilities

• Design and deploy scalable ML systems with real-time inference and monitoring.
• Architect agentic AI systems for autonomous threat detection and policy enforcement.
• Build tools for model development, debugging and explainability.
• Optimize ML workflows for distributed environments with large-scale data.
• Collaborate with security analysts and backend/frontend engineers.
• Advance ML techniques for anti-abuse and account security.

Skills

ML systems

Python

LLMs

Agentic AI

Backend fundamentals

Experimental design

Education

Degree in Computer Science or related field

Job description

You will design and deploy machine learning systems for real-time threat detection and anti-abuse protection, combining ML with security engineering.

Your tasks

• Design and deploy scalable ML systems using modern MLOps practices, including real-time inference and monitoring
• Architect agentic AI systems for autonomous threat detection and adaptive policy enforcement
• Build tools for model development, debugging and explainability
• Optimize ML workflows for distributed environments handling large-scale data
• Collaborate with security analysts and backend/frontend engineers
• Advance ML techniques for anti-abuse and account security

What you bring

• Degree in Computer Science or a related quantitative field
• 2+ years hands-on experience building and running ML systems
• Production-level ML expertise with models at real-world scale
• Hands-on experience with LLMs in agentic environments
• Strong proficiency in Python and backend/server fundamentals
• Deep understanding of probability, hypothesis testing and experimental design

Conditions

• Workload: 100 %
• Work model: On site
• Option of a permanent position after the assignment if both sides want it

What to expect

• 3–6 months interim, then a permanent position

Technologies

• Python
• LLMs