46K–74K EUR / year
Senior Machine Learning Engineer (SOC)
Machine learningOn-site — Paris, Geneva
Published on 2026-10-09
These details were extracted automatically from the original listing. They may not be complete or fully up to date — it's worth checking the original job post.
About this role
Build and deploy machine-learning systems that help Proton’s Security Operations Center detect threats, identify anomalies, and respond more efficiently. The role also includes developing secure data pipelines and may involve LLM-powered automation for analyst workflows.
About the company
Proton builds end-to-end encrypted email, VPN, storage, password, and related privacy tools for individuals and businesses.
The team
Security Operations Center (SOC), collaborating with Proton’s internal Machine Learning team (MSA).
Stack
PythonPandasNumPyAirflowKafkaRedisElasticsearchClickHouse
What you'll do
- Develop and deploy ML models for security detection, anomaly identification, and incident response.
- Integrate model outputs into SOC workflows and tune detections to reduce false positives.
- Build data pipelines that prepare security logs, network traffic, and endpoint events for analysis.
- Prototype threat-detection methods, including anomaly detection and graph-based correlation.
- Develop LLM-powered tools for alert triage, evidence gathering, and incident reporting, with appropriate safeguards.
- Monitor, maintain, and document production models and their performance.
What we're looking for
- Experience in machine-learning engineering or data science, ideally in cybersecurity or operations.
- Proficiency in Python and ML frameworks, plus data analysis with Pandas, NumPy, or similar tools.
- Familiarity with security data such as SIEM logs, EDR telemetry, network flow, or authentication logs.
- Understanding of the ML lifecycle, including preparation, training, evaluation, deployment, and monitoring.
- Experience with data pipelines and storage technologies.
- Ability to work independently and collaborate with ML and security specialists.
Nice to have
- Experience with threat detection, SOC operations, or security automation.
- Knowledge of adversarial ML, graph analytics, or security behavioral modeling.
- Experience integrating ML models into SIEM or automated detection systems.
- Exposure to LLM engineering, including RAG or agent design, and awareness of risks such as prompt injection and data leakage.
Benefits
- Stock options.
- Health coverage, retirement options, generous leave, and wellness support.
- Lunch and snacks at the office.
- Public transport, bike, or parking support.
- Flexible working hours, with an office-first expectation.