AI/ML Lead: Cybersecurity Applications

4 days ago


Thoothukudi, Tamil Nadu, India beBeeCybersecurity Full time ₹ 1,80,00,000 - ₹ 2,00,00,000
AI/ML Lead Job Description

 

  • We are seeking an exceptional AI/ML lead to spearhead the development and implementation of Large Language Models (LLMs) for cybersecurity applications. As a key member of our team, you will be responsible for driving 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. This will involve collaborating with our 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. You will also be responsible for owning 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. This will involve staying 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.

 

Requirements

 

  • 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.


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