Machine Learning Engineer

RemoteMachine Learning

Build models that spot anomalies in attestation, telemetry, and security event data from the field.

What you'll do

Design and train models on attestation, firmware, and platform telemetry
Partner with security research and product on labelled datasets and evaluation metrics
Ship inference pipelines that run reliably in customer environments
Document model limits, false-positive tradeoffs, and monitoring for drift
Improve data collection and labelling workflows with engineering

What you'll bring

Several years building production ML systems, not only notebooks or benchmarks
Strong Python and experience with modern ML frameworks and feature stores
Comfort working with security or infrastructure data that is sparse and imbalanced
Clear communication with non-ML stakeholders on what models can and cannot do
Pragmatic approach to privacy, retention, and customer data boundaries
Helpful: anomaly detection, time-series models, or security analytics backgrounds

What we offer

About Securesil

Securesil builds silicon security solutions that help organisations defend their data, systems, and mission-critical infrastructure. Teams in semiconductors, defence, and critical infrastructure partner with us to embed trust from the chip up. Learn more about Securesil.