Applied AI Engineer

The role

You will build state-of-the-art AI capabilities for a next-generation cybersecurity platform. This involves developing agentic AI systems, machine learning solutions, and training deep learning and LLM models.

What you will do

• Develop state-of-the-art agentic AI systems for next-generation SOC, SOAR, and SIEM platforms.
• Build and optimize large language models (LLMs) for cybersecurity and security operations use cases through post-training techniques.
• Develop domain-specific evaluation frameworks and benchmarks to continuously improve model quality, accuracy, and efficiency.
• Design and implement machine learning and deep learning solutions for security threat detection.
• Develop AI workflows and model pipelines that leverage large-scale security datasets.
• Partner with security researchers to improve data quality, model evaluation, and cybersecurity AI capabilities.
• Collaborate with software engineers to integrate AI models into scalable, production-ready security products.
• Research and apply advancements in LLM architectures, AI agents, model inference, and serving optimization.

Required qualifications

• 5+ years of experience applying machine learning, deep learning, or generative AI to cybersecurity or related domains, and/or a Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or
• Proven track record of applying machine learning, deep learning, or generative AI techniques and delivering high-quality models and solutions into production environments end-to-end.
• Deep understanding of modern AI agent architectures, agent frameworks, and implementation patterns.
• Experience with LLM supervised fine-tuning (SFT), reinforcement learning, preference optimization, and model distillation.
• Strong understanding of supervised and unsupervised learning, reinforcement learning algorithms, model training, and evaluation on large-scale datasets.
• Experience with domain-specific feature engineering, data labeling, and data quality optimization.
• Strong proficiency in Python programming and experience with deep learning frameworks such as PyTorch.
• Familiarity with databases, large-scale data processing systems, and production ML pipelines.
• Strong communication and technical documentation skills.

Nice to have

• Experience with LLM architecture, model pre-training, inference optimization, and model serving infrastructure.
• Experience with big data streaming pipelines, large-scale analytics, and distributed data processing.
• Prior experience applying AI to cybersecurity domains such as threat detection, anomaly detection, fraud detection, malware classification, network traffic analysis, webpage classification, or securit
• Contributions to AI/ML competitions, hackathons, open-source projects, technical blogs, arXiv, or top-tier research publications.

Benefits

• Competitive compensation
• Comprehensive benefits package

Before you apply

• Requires access to information protected under U.S. export control laws and regulations, including EAR and ITAR.
• Employment is conditioned on authorization to receive software or technology controlled under these laws without sponsorship for an export license.

About the company

Cylake-inc is a small team building the next generation of cybersecurity products from the ground up, led by industry veterans.