ML Engineer
Core
Building a new product to detect, govern, and secure AI agents in enterprise Kubernetes infrastructure by analyzing runtime telemetry and behavior.
Role type
Senior IC machine learning engineer (applied AI & security)
Builds
Runtime detection systems, behavioral baselines, and security controls for AI agents
Domain
Cybersecurity, Kubernetes, Applied AI, Distributed Systems
Deliverable
production ML models
Required skills
Production ML system design, classical ML (gradient-boosted trees, classification), anomaly detection, time-series modeling, LLM application (function calling, RAG, fine-tuning), Python, large-scale telemetry data processing
Preferred skills
Security/infrastructure ML, eBPF/kernel telemetry, low-latency inference, model versioning, interpretable ML
Technologies
PyTorch, TensorFlow, scikit-learn, pandas, ClickHouse, BigQuery, Snowflake, Spark, MLflow, BentoML
Responsibilities
Own end-to-end ML modeling for agent detection and risk scoring, design ML systems on existing data infrastructure, lead A/B testing of detection models, act as AI/ML voice in architecture decisions
Seniority
Senior, hands-on IC
