Jobs and Careers

Principal Security ML Research Engineer

United States, United Statesfull_timeVerifiedPosted 29 Jul 2026

About the role

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

What is The Role

As a Principal Security ML Research Engineer on the Threat Research and Detection Engineering team, you'll play a key role in enhancing the Elastic Security threat protections by developing advanced AI and machine learning solutions. In this position, you will address real-world cyber threats. You will use innovative ML detection techniques and effective workflows. You will also work with a diverse team that focuses on research and community involvement. If you’re a skilled professional ready to shape the future of security analytics, this role invites you to make a tangible impact in the field.

What You Will Be Doing

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.

What You Bring

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 fun