Education: Master’s degree or Ph.
in Computer Science, Data Science, Artificial Intelligence, Cybersecurity, or a related highly technical discipline.
Applied Experience: 8+ years of progressive experience in data science, machine learning, or AI engineering, with a minimum of 3 years directly embedded in cybersecurity, threat intelligence, or vulnerability management.
Open-Source AI & LLM Mastery: Deep, hands-on expertise with the Hugging Face ecosystem (Transformers, Accelerate, PEFT).
Proven track record of deploying, quantizing, and fine-tuning (e.
, LoRA, QLoRA) large open-source models (Llama, Mistral, Qwen) for production environments.
Cybersecurity Expertise: Comprehensive understanding of the vulnerability lifecycle, patch gap analysis, exploit chaining, and standard industry frameworks (MITRE ATT&CK, CISA KEV, EPSS, CVSS).
You must understand how an adversary thinks to build models that stop them.
Core ML Frameworks: Expert-level coding proficiency in Python and leading deep learning frameworks, specifically PyTorch.
Infrastructure & Compute: Extensive experience operating in high-performance computing environments.
You must be adept at managing GPU workloads, CUDA optimization, and deploying models on distributed infrastructure (e.
, Kubernetes, Ray, vLLM).
Data Architecture: Strong capability in building high-throughput data pipelines to ingest, clean, and process massive datasets of threat intelligence, code repositories, and telemetry.
Autonomy & Execution: Demonstrated ability to own a complex problem space entirely, translating theoretical data science concepts into highly scalable, real-world defensive tools at an accelerated pace.
Certain states and localities require employers to post a reasonable estimate of salary range.
A reasonable estimate of the current base pay range for this position is $240,000.
00 to $260,000.
00 annually.