low or AWS SageMaker.

Build and maintain dashboards using Grafana, Prometheus or Kibana to track real-time model health and historical trends.

Implement drift detection pipelines using tools like Evidently AI or Alibi Detect to identify shifts in data distributions and trigger alerts or retraining.

Set up centralized logging with ELK Stack or OpenTelemetry to capture AI inference events, errors and audit trails for debugging and compliance.

Develop CI/CD pipelines with GitHub Actions or Jenkins to automate model updates, testing and deployment.

Apply secure-by-design principles to protect data pipelines and models, using encryption, access controls and compliance with regulations like GDPR or NIST AI RMF.

Collaborate with data scientists, AI Integration Engineers and DevOps teams to align model performance with business requirements and infrastructure capabilities.

Optimize models for production via quantization or pruning and ensure efficient resource usage on cloud platforms like AWS, Azure or Google Cloud.

2f:T7cc,{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Security Specialist","description":"

Key Responsibilities

Design and implement end-to-end machine learning pipelines for AI cybersecurity applications.
Deploy and manage machine learning models in production using tools like MLflow, Kubeflow or AWS SageMaker.
Build and maintain dashboards using Grafana, Prometheus or Kibana to track real-time model health and historical trends.
Implement drift detection pipelines using tools like Evidently AI or Alibi Detect to identify shifts in data distributions and trigger alerts or retraining.
Set up centralized logging with ELK Stack or OpenTelemetry to capture AI inference events, errors and audit trails for debugging and compliance.
Develop CI/CD pipelines with GitHub Actions or Jenkins to automate model updates, testing and deployment.
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Machine Learning Security Specialist

Job Type