AI/ML Cybersecurity Solutions Developer

2 days ago

Varanasi, Uttar Pradesh, India beBeeCybersecurity Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Leading the charge in developing cutting-edge cybersecurity solutions, we seek a highly skilled AI/ML expert to spearhead our efforts in training and fine-tuning Large Language Models (LLMs).

This individual will bring a strong background in machine learning, a practical understanding of the cybersecurity domain – especially around threat intelligence, vulnerabilities, exploits, and configuration analysis – and at least 5 years of experience in leading ML projects.

The ideal candidate will be responsible for developing data pipelines to ingest, clean, and structure cybersecurity data, collaborating with cybersecurity analysts to build taxonomy and structured knowledge representations to embed into LLMs, and driving the design and execution of evaluation frameworks specific to cybersecurity tasks.

  • Develop models that understand, process, and generate insights across a wide range of cybersecurity content.
  • 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.
  • Own the lifecycle of model development including training, inference optimization, testing, and deployment.

Required 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.

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.

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