About the Role
Machine Learning Engineer – Classical & Adaptive ML
We are hiring a hands-on Machine Learning Engineer to own the classical ML powering Forge’s detection and triage layer. Forge protects critical Operational Technology (OT) and industrial control environments.
In this individual contributor role, you will build and tune models that score and prioritize security alerts, classify OT assets, and separate real threats from noise—all running directly on local, air-gapped appliances.
Because every deployment operates in a unique, isolated OT environment without access to cloud MLOps services, our models can’t be static artifacts shipped once. You will build
Key Responsibilities
- adaptive machine learning systems
- that learn on the edge, evolving over time based on local traffic patterns and analyst feedback.
- Build and tune XGBoost and gradient boosting models to rank security alerts, drastically cutting false positives and surfacing genuine incidents for analysts.
- Design models that adapt to individual site environments over time using incremental learning, concept drift detection, and human-in-the-loop feedback.
How to Apply
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