Cyber Machine Learning Engineer, Senior

Booz Allen Hamilton•Arlington, VA

1d•$99,000 - $225,000•Onsite

About The Position

Are you interested in accelerating the pace of cyber defense and threat hunting with machine learning? Do you want to be part of a driven, mission-oriented team? As a Cyber Machine Learning Engineer at Booz Allen, you will have an opportunity to contribute to novel and impactful work using your machine learning and cybersecurity expertise to enable and automate near real-time detection and defense for Department of Defense, federal, and commercial clients. You will incorporate open-source tools, innovative methods, and cloud resources to cut down on false positive alerts and time to detection. You will implement continuous integration and delivery to limit manual testing and troubleshooting. You will identify opportunities for effective applications of machine learning to unique cyber defense use cases. You’ll build, train, and package production-ready models in service of detection of advanced persistent threats, adhering to software development best practices. You’ll stay aware of latest research in machine learning and cybersecurity, demonstrating a history of intellectual curiosity and interest towards developing novel solutions for challenging problem sets. The problems we solve are not found in textbooks and require creative solutions. You will work on the cutting edge of operational technologies for cybersecurity settings. This is an opportunity to build your experience in cyber defense and machine learning while developing models and software that will defend the nation. Join our team as we build tools to transform the future. The position is located in Arlington, VA. Join us. The world can’t wait.

Requirements

2+ years of experience with cyber threat hunting and analysis of compromises within security logs, including endpoint and network data
2+ years of experience exploring datasets, training machine learning models to perform inference, and utilizing the output to further cyber investigations
Experience with MITRE ATT&CK framework, MISP threat sharing, or cyber intelligence platforms, including seQure
Experience packaging and deploying production-level models using Python, Bash, Docker, or Kubernetes
Experience with data warehousing, ETL, or data streaming technologies, including Kafka
Experience with SIEM technologies such as Splunk or ElasticSearch
Experience with developing novel solutions for challenging problems
Top Secret clearance
Bachelor’s degree

Nice To Haves

Experience working with large language models (LLMs), natural language processing (NLP), and data science workflows
Experience with data brokers, including Kafka, Confluent, Benthos, RedPanda, or RabbitMQ
Experience with cloud platforms, including Azure, AWS, or GovCloud, or distributed systems
TS/SCI clearance with a polygraph
Master’s degree preferred; Doctorate degree a plus

Responsibilities

Incorporate open-source tools, innovative methods, and cloud resources to cut down on false positive alerts and time to detection.
Implement continuous integration and delivery to limit manual testing and troubleshooting.
Identify opportunities for effective applications of machine learning to unique cyber defense use cases.
Build, train, and package production-ready models in service of detection of advanced persistent threats, adhering to software development best practices.
Stay aware of latest research in machine learning and cybersecurity, demonstrating a history of intellectual curiosity and interest towards developing novel solutions for challenging problem sets.