Principal Security ML Research Engineer

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. As a Principal Security ML Research Engineer, you will enhance threat protections by developing advanced AI and machine learning solutions to address real-world cyber threats.

Responsibilities:

• Design innovative ML architectures that enhance threat detection and response capabilities
• Prototype advanced AI agent workflows to streamline incident investigation processes
• Collaborate with cross-functional teams to define project specifications and ensure models are optimized for real-world performance and accuracy
• Develop machine learning models aimed at detecting behavioral anomalies in security telemetry
• Create techniques for profiling threat actors to better understand and predict their behaviors
• Collaborate with stakeholders to refine security use cases, ensuring the applicability of ML models
• Build evaluation frameworks to assess ML model performance metrics while developing benchmarking pipelines to test for accuracy and latency
• Implement guardrails that minimize false-positive rates in detection systems
• Measure the endurance of models against adversarial attacks and prompt injections, and conduct regular audits of model robustness to report findings to stakeholders
• Mentor senior engineers in machine learning best practices and security methodologies to elevate the team's expertise
• Collaborate closely with Product Management to ensure that security research aligns with product roadmaps
• Foster well-developed relationships with engineering teams to guarantee the seamless implementation of machine learning solutions
• Produce technical blogs that showcase your innovative findings in security machine learning
• Author white papers that tackle emerging threats and detection strategies
• Present insights at industry conferences to share advancements in security ML, and engage with the security research community to promote collaboration and information sharing

Requirements:

• Master's degree in Computer Science, Cybersecurity, or a related field, or 5+ years designing and implementing security machine learning models
• Experience with vector search technology for data retrieval, Retrieval-Augmented Generation techniques, working knowledge of deep learning, clustering, and graph algorithms, and experience training models using scikit-learn, xgboost, PyTorch/Tensorflow
• Knowledge of behavioral anomaly detection in security telemetry and expertise in profiling threat actor behaviors using machine learning
• Ability to develop evaluation frameworks for ML model performance metrics and experience with benchmarking pipelines for testing accuracy and latency
• Experience developing industry-leading scalable machine learning models that significantly improved threat detection while ensuring minimal false-positive rates
• Published research in reputable security and machine learning journals or presented findings at major security conferences and workshops
• Proficiency in modern AI/ML frameworks and hands-on experience integrating LLM APIs into production applications
• You possess the ability to comfortably rotate across projects, collaborate across functions and teams, and seamlessly adapt to evolving team structures
• Proven ability to seamlessly transition between different projects, codebases, or scrum teams based on dynamic business priorities
• You work autonomously and can drive decisions and results in a distributed team by leveraging asynchronous, direct, and transparent communication