Full Stack AI Engineer - Security

Ryz Labs; Buenos Aires; Teletrabalho; BRL 414 292 - 621 439; Tempo integral

Resumo da oferta

A cybersecurity firm is seeking a Security AI Engineer to design and deploy AI systems that protect their platforms. This role encompasses developing intelligent defenses against security threats through machine learning and close collaboration with security and infrastructure teams. The ideal candidate should have strong experience in machine learning and a solid understanding of security concepts. This position offers a remote work opportunity for professionals based in Argentina or Uruguay.

Qualificações

• Bachelor’s degree in Computer Science or Engineering; Master’s preferred.
• Strong experience in machine learning with production deployment.
• Solid foundation in security concepts like threat modeling.
• Proficiency in Python and popular ML frameworks.
• Experience with large-scale data systems.

Responsabilidades

• Design and implement AI models to detect security threats.
• Build and maintain data pipelines for model training.
• Integrate AI security solutions into production systems.
• Monitor model performance and improve detection accuracy.
• Research emerging threats and adapt defenses.

Conhecimentos

Machine learning

Cybersecurity

Python

Data systems

Adversarial ML

Formação académica

Bachelor’s degree in Computer Science or related field

Master’s degree preferred

Ferramentas

PyTorch

TensorFlow

scikit-learn

Descrição da oferta de emprego

Remote position, only for professionals based in Argentina or Uruguay.

At Ryz Labs we are looking for a Security AI Engineer to design, build, and deploy AI-driven systems that protect one of our team's platforms, users, and data. You’ll sit at the intersection of machine learning, cybersecurity, and engineering—developing intelligent defenses against threats such as fraud, abuse, intrusion, and data leakage.

This role blends hands‑on ML development with real‑world security problem‑solving and close collaboration with security, infrastructure, and product teams.

Essential Responsibilities

• Design and implement AI/ML models to detect, prevent, and respond to security threats (e.g., fraud, abuse, anomalies, malware, insider risk).
• Build and maintain pipelines for data ingestion, feature engineering, model training, evaluation, and deployment.
• Apply techniques such as anomaly detection, graph analysis, NLP, and behavioral modeling to security use cases.
• Integrate AI security solutions into production systems with high reliability and low latency.
• Partner with Security, DevOps, and Platform teams to embed AI‑driven protections into existing tools and workflows.
• Monitor model performance, address drift, and continuously improve detection accuracy and resilience.
• Research emerging threats and adversarial techniques, including adversarial ML, and proactively adapt defenses.
• Contribute to incident response by providing AI‑based insights and automation.

Qualifications / Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field; Master’s degree preferred.
• Strong experience in machine learning or applied AI, with production deployment experience.
• Solid foundation in security concepts (e.g., threat modeling, authentication, authorization, network or application security).
• Proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, scikit‑learn).
• Experience working with large‑scale data systems (SQL/NoSQL, streaming pipelines, logs, telemetry).
• Familiarity with cloud platforms and MLOps practices (CI/CD, monitoring, model lifecycle management).
• Ability to reason about trade‑offs between security, performance, and usability.

Knowledge, Skills, and Abilities Required

• Background in cybersecurity, fraud detection, trust & safety, or abuse prevention.
• Experience with graph‑based ML, NLP for security signals, or time‑series anomaly detection.
• Knowledge of adversarial ML, model evasion techniques, or secure model design.
• Experience building systems that operate under strict latency or reliability constraints.
• Prior work in regulated or high‑risk environments.
• Security certifications or coursework (e.g., OSCP, CISSP concepts).
• Experience with SIEM/SOAR tools or security telemetry platforms.
• Publications, talks, or open‑source contributions in AI or security.