
Senior Machine Learning Engineer
2 days ago
We are seeking an accomplished machine learning strategist with a strong background in training and fine-tuning large language models (LLMs). The ideal candidate will possess experience working with frameworks such as vLLM, HuggingFace Transformers, LoRA/QLoRA, and distributed training techniques.
Key responsibilities include:
- Fine-tuning and domain adaptation of open-source LLMs using advanced techniques.
- Developing data pipelines to ingest, clean, and structure cybersecurity data from sources like MITRE ATT&CK, CVE/NVD databases, YARA rules, Snort/Suricata rules, STIX/TAXII, or malware datasets.
- Collaborating with cybersecurity analysts to build taxonomy and structured knowledge representations.
- Driving the design and execution of evaluation frameworks for cybersecurity tasks.
- Owning the lifecycle of model development including training, inference optimization, testing, and deployment in production environments.
To be successful in this role, you should have:
- A minimum of 5 years of experience in machine learning, with at least 2 years focused on LLM training or fine-tuning.
- Strong expertise in vLLM, HuggingFace Transformers, LoRA/QLoRA, and distributed training techniques.
- Experience working with cybersecurity data, including understanding of common tools and frameworks.
- Proficiency in Python, ML libraries (PyTorch, Transformers), and MLOps practices.
This position offers:
- The opportunity to work with cutting-edge technologies and contribute to the development of innovative solutions.
- A dynamic and collaborative work environment.
- A competitive compensation package.
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