AL/ML Lead

Job Description :

Were looking for a skilled Al/ML lead ( 5+ years) based out of Chennai, for a global computer and network security company.

Deep experience in training and fine-tuning Large Language Models (LLMs) such as LLaMA 3 using frameworks like vLLM. 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.

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 the fine-tuning and domain adaptation of open-source LLMs (e.g., LLaMA 3) 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 Qualifications :

- 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.

Nice to Have :

- 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.