ML Scientist

📋 Description

• Work side by side with the Security team to understand current and emerging attack techniques
• Explore and analyze our telemetry (datalake on ClickHouse and S3) to uncover signals, patterns, and
• Design, prototype, and evaluate attack detection and prevention models: anomaly detection
• Define how success is measured: detection metrics, acceptable false-positive rates, and evaluation
• Take validated prototypes toward production in collaboration with the engineering team, and lay the
• Stay current with research in ML applied to security (anomaly detection, adversarial ML, fraud) and

🎯 Requirements

• Proven experience (5+ years, or PhD plus applied experience) researching and developing ML models
• Strong command of anomaly detection and unsupervised / semi-supervised learning: labeled data is
• Experience with large-scale telemetry or event data: logs, time series, user or device behavior
• Full autonomy with raw data: solid Python (pandas/polars, scikit-learn, PyTorch or similar)
• Product mindset: the ability to go from a research idea to an evaluable prototype in weeks, not
• Genuine curiosity about cybersecurity and the drive to learn the domain in depth alongside the

🎁 Benefits

• The chance to define the company's ML strategy from scratch, with direct product impact and full
• A technically fascinating problem: a real adversary that evolves, massive untapped data, and
• Daily collaboration with a Security team with deep domain expertise.
• Optimized onboarding – for your optimal start and customized induction.
• Technical ownership – take responsibility for key components and shape how we build our platform.
• Enthusiastic team – waiting to help you succeed and collaborate with experienced engineers.