AL/ML lead

We’re looking for a skilled Al/ML lead ( 5+ years) based out of Chennai, for a global computer and network security company.Deep experience intraining and fine-tuning Large Language Models (LLMs)such as LLaMA 3 using frameworks likevLLM . The ideal candidate will bring a strong background in machine learning and a practical understanding of the cybersecurity domain—especially aroundthreat intelligence, vulnerabilities, exploits, and configuration analysis .You will lead the development and implementation of models that understand, process, and generate insights across a wide range of cybersecurity content. You will guide a team of ML engineers and collaborate closely with cybersecurity SMEs, data engineers, and DevOps to ensure delivery of scalable, performant, and security-aware AI systems.Key Responsibilities Lead thefine-tuning and domain adaptationof open-source LLMs (e.g., LLaMA 3) using frameworks likevLLM, HuggingFace, DeepSpeed, and PEFT techniques . Develop data pipelines to ingest, clean, and structure cybersecurity data, includingthreat intelligence reports, CVEs, exploits, malware analysis, and configuration files . Collaborate with cybersecurity analysts to buildtaxonomy and structured knowledge representationsto embed into LLMs. Drive the design and execution ofevaluation frameworksspecific to cybersecurity tasks (e.g., classification, summarization, anomaly detection). Own the lifecycle of model development includingtraining, 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 Qualifications 5+ years of experience inmachine learning , with at least 2 years focused onLLM training or fine-tuning . Strong experience withvLLM, HuggingFace Transformers, LoRA/QLoRA, and distributed training techniques . Proven experience working withcybersecurity data —ideally includingMITRE ATT&CK, CVE/NVD databases, YARA rules, Snort/Suricata rules, STIX/TAXII, or malware datasets . Proficiency inPython , 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.Nice to Have Experience deploying models viavLLMin production environments withFastAPI or similar APIs . Knowledge ofcloud-based ML training(AWS/GCP/Azure) and GPU infrastructure. Background inreverse 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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