(Security) Machine Learning Engineer

Requirements

  • Proven experience in machine learning engineering or data science, ideally in a cybersecurity or operations context.
  • Proficiency in Python, with strong knowledge of ML frameworks.
  • Experience with data manipulation and analysis using Pandas, NumPy or similar tools.
  • Familiarity with security data sources (e.g., SIEM logs, EDR telemetry, network flow, authentication logs).
  • Solid understanding of ML lifecycle: data preparation, model training, evaluation, deployment, and monitoring.
  • Experience with data pipelines and storage technologies (e.g., Airflow, Kafka, Redis, Elasticsearch, Clickhouse, etc.).
  • Ability to work independently and collaborate effectively with both ML and security specialists.

Nice to Haves

  • Prior experience in threat detection, SOC operations, or security automation.
  • Knowledge of adversarial ML, graph analytics, or behavioral modeling in security contexts.
  • Experience integrating ML models into SIEM pipelines or automated detection frameworks.
  • Exposure to LLMs and AI engineering (e.g., prompt engineering, RAG, agent design), and awareness of LLM-specific risks like prompt injection and data leakage.

What You'll Be Doing

  • Design, develop, and deploy machine learning models to enhance security detection, anomaly identification, and incident response.
  • Integrate ML outputs into the SOC workflow to enable smarter and faster triage.
  • Continuously evaluate and tune models to reduce false positives and improve detection precision.
  • Ensure model outputs are interpretable and actionable for SOC analysts.

Perks and Benefits

  • Work that Matters: millions of people trust Proton with their privacy.
  • Technology: you'll get the right hardware and software you need.
  • Learning & Development: we invest in your growth.
  • Employee Benefits: strong health coverage, retirement options, generous leave, and wellness support.
  • Stock Options: opportunity to be owners of the company.
  • In-Person Collaboration: offices across multiple locations for face-to-face collaboration.
  • Food: Lunch and snacks provided daily in offices.
  • Transport: Public transport, bike allowances, or parking covered.
  • Flexible Working: Own your schedule.
AI Summary ✨

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