Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Designing and deploying scalable ML and agentic AI systems for anti-abuse and account security with an accent on MLOps, real-time inference, and adversarial robustness. Focus on building autonomous threat detection pipelines, optimizing distributed systems for large-scale data, and advancing privacy-preserving AI techniques.

Location: Must be based in or able to work onsite in Geneva or Taipei

Company

hirify.global is an independent, mission-driven organization founded by CERN scientists, dedicated to making privacy the default through a suite of encrypted tools used by millions worldwide.

What you will do

• Design and deploy scalable ML systems using modern MLOps practices.
• Architect agentic AI systems for autonomous threat detection and response.
• Build robust tools for model development, debugging, and explainability.
• Optimize ML workflows for distributed environments to handle large-scale data.
• Collaborate cross-functionally with security, engineering, and support teams.
• Advance anti-abuse techniques using adversarial robustness and graph-based detection.

Requirements

• Degree in Computer Science or quantitative field.
• 2+ years of hands-on experience in building and running ML systems.
• Proven production-level ML expertise at scale.
• Practical experience with LLMs in agentic environments.
• Strong software engineering skills with proficiency in Python.
• Deep understanding of probability, experimental design, and statistical rigor.

Nice to have

• Experience with adversarial ML or red-teaming.
• Contributions to open-source security or privacy tools.
• Knowledge of federated learning, differential privacy, or graph-based anomaly detection.
• Technical leadership experience owning projects and mentoring peers.

Culture & Benefits

• Meaningful, mission-driven work with global scale impact.
• Employee stock options granting ownership in the company.
• Supportive learning and development environment with professional growth opportunities.
• Comprehensive health coverage and wellness support.
• Daily catered lunches and snacks in the office.
• Commuter benefits including public transport or bike allowances.