Full-Time Sr Principal Machine Learning Engineer (Cortex)

We're seeking a talented and experienced Sr Principal AI Researcher to join the Cortex Foundational Artificial Intelligence Research Team. Our team mission is to make leading-edge AI systems perform better at cybersecurity.

We are building and improving foundational capabilities in cybersecurity systems using Large Language Models, Reasoning Models, Generative AI, Knowledge Graphs, Agentic AI, Model Fine-tuning/Distilling, and Retrieval Augmented Generation to be leveraged for future cybersecurity products.

The ideal candidate enjoys collaboration, open-ended problem solving, and rolling up your sleeves to find a pragmatic solution that pushes the team and our mission forward.

This role does not require prior Cybersecurity expertise, but you will definitely learn about Cybersecurity technology on the job.

Advance the state of the art in Cybersecurity through applied research in Large Language Models, Transformer-based Encoders, Natural Language and Structured Data Processing, Generative AI, Agentic AI, and Deep Learning.

Design and implement research experiments to demonstrate increased accuracy, efficiency, and helpfulness of novel AI systems and techniques.

Train and fine-tune large-scale language models using GPU-accelerated infrastructure.

Develop and implement evaluation metrics for assessing model quality, efficiency, and robustness.

Stay at the forefront of AI advancements and integrate state-of-the-art techniques into our models.

Collaborate with engineers to translate research into production-ready AI systems.

Communicate with AI experts throughout the organization to share research findings and technical progress.

Publish findings in top-tier AI/ML conferences and journals, and participate in relevant conferences and workshops.

Required Experience

• Published research in AI/ML, with an advanced degree.
• 7+ years of relevant experience in AI
• Proven expertise in training, fine-tuning, and evaluating LLMs.
• Proficiency in deep learning frameworks, distributed training techniques, and large-scale datasets.
• Excellent research programming skills in Python and familiarity with CUDA, TensorRT, or other GPU optimization tools.
• Strong working knowledge of machine learning algorithms.
• Strong problem-solving skills and the ability to work independently and collaboratively

Ideal Candidate

• Experience with transformer models.
• Knowledge of model distillation, quantization, or pruning techniques
• Experience with distributed cloud systems and containerization tools
• Previous experience applying AI/ML techniques to cybersecurity problems
• Knowledge of data privacy and security considerations in AI

Compensation

The compensation will depend on qualifications, experience, and work location. Starting base salary (non-sales) is expected to be between $170,000 - $277,000/YR.

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