ML Detection Engineer

Arcitix Security; United States; On-site; USD 100,000 - 130,000; Full time

Job summary

Arcitix Technologies in the United States is looking for ML Detection Engineers to develop machine-learning models that enhance threat detection capabilities. The role requires collaboration with SOC analysts to engineer features and operationalize models efficiently.

The ideal candidate has a degree in computer science or machine learning, with over 4 years of experience in ML engineering applied to security. Strong Python skills and familiarity with security telemetry are essential, along with the ability to work on real-time inference systems.

Qualifications

• 4+ years in ML engineering, ideally applied to security.
• Experience deploying and monitoring models in production.

Responsibilities

• Develop and tune ML models for anomaly and threat detection.
• Engineer features from identity, endpoint, network, and cloud telemetry.
• Reduce false positives while preserving detection coverage.
• Operationalize models through detection-as-code pipelines.
• Partner with the SOC to measure and improve detection effectiveness.

Skills

Python

Machine Learning frameworks

Understanding of attacker TTPs

Security Telemetry

Streaming data

Education

Bachelor's or Master's in CS, ML, or related field

Job description

Build the machine-learning models that power our threat detection — behavioral analytics, anomaly detection, and detection-as-code.

About the role

ML Detection Engineers build the models that let our agentic SOC see what signature-based tools miss. You will engineer features from identity, endpoint, and cloud telemetry, train and tune detection models, and operationalize them as detection-as-code that runs at scale.

You will work shoulder-to-shoulder with SOC analysts and threat researchers, closing the loop between what attackers actually do and what our models learn to catch.

Key Responsibilities

• Develop and tune ML models for anomaly and threat detection
• Engineer features from identity, endpoint, network, and cloud telemetry
• Reduce false positives while preserving detection coverage
• Operationalize models through detection-as-code pipelines
• Partner with the SOC to measure and improve detection effectiveness

Requirements

• Bachelor's or Master's in CS, ML, or a related field
• 4+ years in ML engineering, ideally applied to security
• Strong Python and experience with modern ML frameworks
• Understanding of attacker TTPs and security telemetry
• Experience deploying and monitoring models in production

Nice to have

• Experience with streaming data and real-time inference
• Familiarity with SIEM/data-lake architectures
• Knowledge of adversarial ML and model evasion