Security ML Engineer: Proactive Threat Detection

Proton; Genf; On-site; CHF 120,000 - 180,000; Full time

Benefits offered by this job

Health coverage

Stock options

Flexible schedule

Office across Geneva

Job summary

Proton is seeking a Security Machine Learning Engineer to advance our SOC from reactive to proactive through ML-driven detection and data-driven analytics. You will work within the security team and collaborate with the internal ML group to deploy scalable models that identify threats and automate analyst workflows.

The role combines cybersecurity operations with modern ML engineering, including data pipelines, model deployment, and governance.

Qualifications

• Proven experience in machine learning engineering or data science, ideally in cybersecurity or operations.
• Proficiency in Python, with strong knowledge of ML frameworks.
• Experience with data manipulation using Pandas/NumPy or similar.
• Familiarity with security data sources (SIEM, EDR, network logs).
• Solid understanding of the ML lifecycle: data prep, training, evaluation, deployment, monitoring.
• Experience with data pipelines and storage tech (Airflow, Kafka, Redis, Elasticsearch, Clickhouse).
• Ability to work independently and collaborate with ML and security specialists.

Responsibilities

• Design, develop, and deploy ML models to enhance security detection and incident response.
• Build and maintain data pipelines to convert logs and events into ML-ready datasets.
• Explore and build LLM-powered tools to automate SOC tasks and analyst workflows.
• Stay current on security data science and adversarial ML developments.
• Deploy models securely, with monitoring and retraining for reliability.

Skills

ML engineering

Python

Pandas/NumPy

Security data sources

ML lifecycle

Data pipelines/storage

Independent work

Tools

Airflow

Kafka

Redis

Elasticsearch

Clickhouse

Job description

Proton is seeking a Security Machine Learning Engineer to advance our SOC from reactive to proactive through ML-driven detection and data-driven analytics. You will work within the security team and collaborate with the internal ML group to deploy scalable models that identify threats and automate analyst workflows.

The role combines cybersecurity operations with modern ML engineering, including data pipelines, model deployment, and governance.