Chief Cybersecurity Model Architect

1 week ago

Dombivli, Maharashtra, India beBeeCybersecurity Full time ₹ 2,50,00,000 - ₹ 3,00,00,000
Large Language Model Lead Position

Job Summary:

This role focuses on driving the development and implementation of Large Language Models (LLMs) utilizing frameworks such as vLLM, HuggingFace, DeepSpeed, and PEFT techniques.

Key Responsibilities:

  • Lead the training and fine-tuning of Large Language Models using cutting-edge frameworks like vLLM.
  • Develop robust 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 create taxonomy and structured knowledge representations for embedding into LLMs.
  • Design and execute evaluation frameworks tailored to cybersecurity tasks such as classification, summarization, and anomaly detection.
  • Oversee the entire model development lifecycle, from training to inference optimization, testing, and deployment.
  • Provide technical guidance and mentorship to a team of ML engineers and researchers.
  • Stay up-to-date with advancements in LLM architectures, cybersecurity datasets, and AI-based threat detection.
  • Advocate for responsible AI use and ensure model robustness, particularly given the sensitive nature of cybersecurity data.

Required Qualifications:

  • A minimum of 5 years of experience in machine learning, with at least 2 years focused on LLM training or fine-tuning.
  • Strong expertise in vLLM, HuggingFace Transformers, LoRA/QLoRA, and distributed training techniques.
  • Proven experience working with various types of cybersecurity data, preferably including MITRE ATT&CK, CVE/NVD databases, YARA rules, Snort/Suricata rules, STIX/TAXII, or malware datasets.
  • Proficiency in Python, popular ML libraries (PyTorch, Transformers), and MLOps best practices.
  • Familiarity with prompt engineering, RAG (Retrieval-Augmented Generation), and vector stores like FAISS or Weaviate.
  • Demonstrated leadership skills and ability to collaborate effectively with interdisciplinary teams.
  • Excellent problem-solving skills and strong written & verbal communication abilities.

Nice to Have:

  • Experience deploying models via vLLM in production environments using FastAPI or similar APIs.
  • Knowledge of cloud-based ML training platforms (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.

Essential Job Requirements:

  • At least 5 years of experience in machine learning, with at least 2 years focused on LLM training or fine-tuning.
  • Deep expertise in training and fine-tuning Large Language Models (LLMs) using frameworks like vLLM.

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