Cybersecurity AI Specialist

6 days ago

Thāne, Maharashtra, India beBeecybersecurity Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Machine Learning and Cybersecurity Lead

About the Job:

We're seeking an experienced Machine Learning (ML) expert to join our team. The ideal candidate will have a strong background in machine learning and a practical understanding of the cybersecurity domain.

The ML lead will be responsible for developing and implementing models that understand, process, and generate insights across a range of cybersecurity content. They'll guide a team of ML engineers and collaborate closely with cybersecurity SMEs, data engineers, and DevOps to ensure delivery of scalable, performant, and security-aware AI systems.

Main Responsibilities:

  1. Lead the fine-tuning and domain adaptation of open-source Large Language Models (LLMs) using frameworks like vLLM, HuggingFace, DeepSpeed, and PEFT techniques.
  2. Develop data pipelines to ingest, clean, and structure cybersecurity data, including threat intelligence reports, CVEs, exploits, malware analysis, and configuration files.
  3. Collaborate with cybersecurity analysts to build taxonomy and structured knowledge representations to embed into LLMs.
  4. Drive the design and execution of evaluation frameworks specific to cybersecurity tasks (e.g., classification, summarization, anomaly detection).
  5. Own the lifecycle of model development including training, inference optimization, testing, and deployment.
  6. Provide technical leadership and mentorship to a team of ML engineers and researchers.
  7. Stay current with advances in LLM architectures, cybersecurity datasets, and AI-based threat detection.
  8. Advocate for ethical AI use and model robustness, especially given the sensitive nature of cybersecurity data.

Required Skills and 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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