AI Cybersecurity Lead

22 hours ago

Erode, Tamil Nadu, India beBeeCybersecurity Full time US$ 1,80,000 - US$ 2,50,000

Job Title: Senior AI Cybersecurity Engineer

Description:

We are seeking an experienced Senior AI Cybersecurity Engineer to lead our team in developing and implementing cutting-edge AI models for cybersecurity. The ideal candidate will have a strong background in machine learning, deep experience in training and fine-tuning Large Language Models (LLMs), and a practical understanding of the cybersecurity domain.

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, such as classification, summarization, and anomaly detection.
  • 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.
  • Advocate for ethical AI use and model robustness, especially given the sensitive nature of cybersecurity data.

Required Skills & Qualifications:

  • 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 (PyTorch, Transformers), and MLOps practices.
  • Familiarity with prompt engineering, RAG (Retrieval-Augmented Generation), and vector stores like FAISS or Weaviate.
  • Demonstrated ability to lead projects and collaborate across interdisciplinary teams.
  • Excellent problem-solving skills and strong written & verbal communication.

Nice to Have:

  • Experience deploying models via vLLM in production environments with FastAPI or similar APIs.
  • Knowledge of cloud-based ML training (AWS/GCP/Azure) and GPU infrastructure.
  • Background in reverse engineering, malware analysis, red teaming, or threat hunting.
  • Publications, open-source contributions, or technical blogs in the intersection of AI and cybersecurity.

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