Cybersecurity Machine Learning Specialist

4 days ago

Allahabad, Uttar Pradesh, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Machine Learning Expert

We are seeking a seasoned expert with 5+ years of experience to lead our cybersecurity team based out of Chennai.

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.

This role involves leading the development and implementation of models that understand, process, and generate insights across a wide range of cybersecurity content.

Key Responsibilities:
  • Lead 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.
  • 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.
  • 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.
  • Proficiency in Python, ML libraries (PyTorch, Transformers), and MLOps practices.

Benefits:

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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