Data Scientist

4 days ago

Malappuram, Kerala, India beBeeCybersecurity Full time ₹ 1,80,00,000 - ₹ 2,40,00,000

Job Title: Cybersecurity Model Lead

About the Role

We are seeking a skilled professional to lead our team in developing and implementing models that understand, process, and generate insights across a wide range of cybersecurity content.

Key Responsibilities
  • Develop and fine-tune open-source Large Language Models (LLMs) using frameworks like vLLM, HuggingFace, DeepSpeed, and PEFT techniques.
  • Design and implement 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 (e.g., classification, summarization, 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.
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.
  • Demonstrated ability to lead projects and collaborate across interdisciplinary teams.
  • Excellent problem-solving skills and strong written & verbal communication.

The ideal candidate will bring a strong background in machine learning and a practical understanding of the cybersecurity domain—especially around threat intelligence, vulnerabilities, exploits, and configuration analysis.

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