
Cybersecurity Expert Leader
7 days ago
We are seeking a highly skilled Artificial Intelligence leader to join our organization.
The ideal candidate will have deep experience in training and fine-tuning Large Language Models (LLMs) using frameworks like vLLM. A strong background in machine learning and practical understanding of the cybersecurity domain is essential, particularly around threat intelligence, vulnerabilities, exploits, and configuration analysis.
This role involves leading the development and implementation of models that understand, process, and generate insights across a wide range of cybersecurity content. You will collaborate closely with ML engineers, cybersecurity SMEs, data engineers, and DevOps to ensure delivery of scalable, performant, and security-aware AI systems.
Key Responsibilities
- Lead the fine-tuning and domain adaptation of open-source LLMs using frameworks like vLLM, HuggingFace, DeepSpeed, and PEFT techniques.
- Develop data pipelines to ingest, clean, and structure cybersecurity data, including threat intelligence reports, CVEs, exploits, malware analysis, and configuration files.
- Collaborate with cybersecurity analysts to build taxonomy and structured knowledge representations to embed into LLMs.
- Drive the design and execution of evaluation frameworks specific to cybersecurity tasks.
- Own the lifecycle of model development including training, inference optimization, testing, and deployment.
- Provide technical leadership and mentorship to a team of ML engineers and researchers.
- Stay current with advances in LLM architectures, cybersecurity datasets, and AI-based threat detection.
Required Skills
- 5+ years of experience in machine learning, with at least 2 years focused on LLM training or fine-tuning.
- Strong experience with vLLM, HuggingFace Transformers, LoRA/QLoRA, and distributed training techniques.
- Proven experience working with cybersecurity data—ideally including MITRE ATT&CK, CVE/NVD databases, YARA rules, Snort/Suricata rules, STIX/TAXII, or malware datasets.
- Proficiency in Python, ML libraries, and MLOps practices.
- Familiarity with prompt engineering, RAG, and vector stores.
Benefits
This position offers the opportunity to lead projects and collaborate across interdisciplinary teams.
Excellent problem-solving skills and strong written & verbal communication are essential for this role.
Nice to Have
- Experience deploying models via vLLM in production environments.
- Knowledge of cloud-based ML training and GPU infrastructure.
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