Senior Machine Learning Engineer
4 days ago
Synarc seeks a seasoned expert in leading the development and implementation of sophisticated AI systems for cybersecurity. The ideal candidate will have a deep background in machine learning, particularly in training and fine-tuning Large Language Models (LLMs), as well as strong expertise in the cybersecurity domain.
Key Responsibilities- Fine-tune open-source LLMs using frameworks like vLLM, HuggingFace, DeepSpeed, and PEFT techniques.
- Design and implement data pipelines to ingest, clean, and structure cybersecurity data.
- Collaborate with cybersecurity analysts to build taxonomy and structured knowledge representations for embedding into LLMs.
- Develop evaluation frameworks for cybersecurity tasks such as classification, summarization, and anomaly detection.
- Lead 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.
- 5+ years of experience in machine learning, with at least 2 years focused on LLM training or fine-tuning.
- Strong experience with distributed training techniques, including vLLM, HuggingFace Transformers, LoRA/QLoRA.
- Proven expertise working with cybersecurity data, including threat intelligence reports, CVEs, exploits, malware analysis, and configuration files.
- 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.
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