Senior Machine Learning Engineer
3 days ago
We're seeking an exceptional Lead Data Scientist to spearhead the development and implementation of Large Language Models (LLMs) for cybersecurity applications. The ideal candidate will bring a strong background in machine learning and a practical understanding of the cybersecurity domain.
The successful candidate will be responsible for:
- Leading the fine-tuning and domain adaptation of open-source LLMs using frameworks like vLLM, HuggingFace, DeepSpeed, and PEFT techniques.
- Developing data pipelines to ingest, clean, and structure cybersecurity data, including threat intelligence reports, CVEs, exploits, malware analysis, and configuration files.
- Collaborating with cybersecurity analysts to build taxonomy and structured knowledge representations to embed into LLMs.
- Driving the design and execution of evaluation frameworks specific to cybersecurity tasks, such as classification, summarization, and anomaly detection.
- Own the lifecycle of model development, including training, inference optimization, testing, and deployment.
- Providing technical leadership and mentorship to a team of ML engineers and researchers.
- 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, 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.
- 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.
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