Cybersecurity Machine Learning Specialist

5 days ago

Guntur, Andhra Pradesh, India beBeeExpert Full time ₹ 1,50,00,000 - ₹ 1,75,00,000
Machine Learning Expert Wanted

We are seeking an experienced Machine Learning professional to join our organization.

The ideal candidate will have a strong background in machine learning, particularly in training and fine-tuning Large Language Models (LLMs). Experience with frameworks like vLLM, HuggingFace Transformers, LoRA/QLoRA, and distributed training techniques is highly desirable.

In this role, you will lead the development and implementation of models that understand, process, and generate insights across various cybersecurity content. You will work closely with ML engineers, cybersecurity SMEs, data engineers, and DevOps teams to ensure delivery of scalable, performant, and security-aware AI systems.

Key Responsibilities
  • Fine-tune and domain adapt open-source LLMs using vLLM, HuggingFace, DeepSpeed, and PEFT techniques.
  • Develop pipelines to ingest, clean, and structure cybersecurity data, including threat intelligence reports, CVEs, exploits, malware analysis, and configuration files.
  • Collaborate with analysts to build taxonomy and structured knowledge representations for embedding into LLMs.
  • Design and execute evaluation frameworks specific to cybersecurity tasks, such as classification, summarization, and anomaly detection.
  • Oversee model development lifecycle, including training, inference optimization, testing, and deployment.
  • Provide technical leadership and mentorship to ML engineers and researchers.
  • Stay up-to-date with advances in LLM architectures, cybersecurity datasets, and AI-based threat detection.
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, 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.

This opportunity aligns with our strategic goals and allows you to contribute to cutting-edge AI research and development.

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