Machine Learning Engineer, Information Security

What you'll do

• Develop and deploy production-ready AI/ML systems using internal platforms, cloud services, and local compute environments.
• Translate research into practical machine learning models for specific security use cases.
• Implement generative AI, statistical modeling, and reinforcement learning to address complex security challenges.
• Manage end-to-end ML workflows including data exploration, model development, evaluation metrics design, deployment, and monitoring.
• Build and scale AI/ML driven solutions to detect and prevent advanced cyber threats.
• Develop and maintain automated machine learning pipelines within CI/CD workflows.
• Deploy models on CUDA devices using frameworks like TensorFlow or PyTorch.
• Integrate ML models into core security processes such as incident response, threat intelligence, and vulnerability management.

What we're looking for

• Bachelor's or Master's degree in Machine Learning, Data Science, Computer Science, Information Security, Mathematics, Statistics, or a related field.
• Ph.D. in a technical field such as Computer Science, Engineering, Statistics, or related disciplines (preferred).
• Strong programming skills in Python and Scala with experience using libraries like TensorFlow, PyTorch, HuggingFace, and Scikit-learn.
• Hands-on experience with the full ML model lifecycle including experimentation, deployment, and monitoring.
• Solid grasp of security fundamentals such as network security, incident response, threat modeling, and vulnerability management.
• Experience deploying models on CUDA devices and operating production services in cloud native environments.
• Proven experience building generative AI applications for real-world use cases.
• Proficiency in additional areas like large language models, Spark, C++, Swift, or specific cybersecurity tools (preferred).