AI/Machine Learning Leader

21 hours ago

Thiruvananthapuram, Kerala, India beBeeCybersecurity Full time ₹ 1,80,00,000 - ₹ 2,50,00,000
Job Overview">

Role Summary:

">

We are seeking an accomplished AI/ML leader to drive the development and implementation of large language models that understand, process, and generate insights across a wide range of cybersecurity content.

">Key Responsibilities">
  • ">
  • Fine-Tuning and Domain Adaptation: Lead the fine-tuning and domain adaptation of open-source llms using frameworks like VLLM, HuggingFace, DeepSpeed, and Peft techniques.">
  • Data Pipelines: Develop data pipelines to ingest, clean, and structure cybersecurity data, including threat intelligence reports, CVEs, exploits, malware analysis, and configuration files.">
  • Collaboration and Knowledge Representation: Collaborate with cybersecurity analysts to build taxonomy and structured knowledge representations to embed into llms.">
  • Evaluation Frameworks: Drive the design and execution of evaluation frameworks specific to cybersecurity tasks, such as classification, summarization, anomaly detection.">
  • Model Development Lifecycle: Own the lifecycle of model development, including training, inference optimization, testing, and deployment.">
  • Technical Leadership: Provide technical leadership and mentorship to a team of ML engineers and researchers.">
  • Staying Current: Stay current with advances in LLM architectures, cybersecurity datasets, and AI-based threat detection.">
  • Ethical AI Use: Advocate for ethical AI use and model robustness, especially given the sensitive nature of cybersecurity data.">
    • ">Required Skills and Qualifications">
      • ">
      • Machine Learning Experience: 5+ years of experience in machine learning, with at least 2 years focused on LLM training or fine-tuning.">
      • Programming Skills: Strong experience with VLLM, HuggingFace Transformers, LoRaRa/QLoRa, and distributed training techniques.">
      • Cybersecurity Data: Proven experience working with cybersecurity data—ideally including MITRE ATT&CK, CVE/NVD databases, Yara rules, Snort/Suricata rules, STIX/TAXII, or malware datasets.">
      • Python Proficiency: Proficiency in Python, ML libraries (PyTorch, Transformers), and MLOps practices.">
      • Prompt Engineering: Familiarity with prompt engineering, RAG (Retrieval-Augmented Generation), and vector stores like Faiss or Weaviate.">
      • Leadership and Communication: Demonstrated ability to lead projects and collaborate across interdisciplinary teams. Excellent problem-solving skills and strong written & verbal communication.">
        • ">Nice to Have">
          • ">
          • Deployment Experience: Experience deploying models via VLLM in production environments with FastAPI or similar APIs.">
          • Cloud-Based ML Training: Knowledge of cloud-based ML training (AWS/GCP/Azure) and GPU infrastructure.">
          • Reverse Engineering: Background in reverse engineering, malware analysis, red teaming, or threat hunting.">
          • Publications: Publications, open-source contributions, or technical blogs in the intersection of AI and cybersecurity.">
          "],

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