Job Description

Remote Work:
Hybrid
Job Number:
R0231625
Location:
Washington,DC,US
Additional Locations:
  • Alexandria, Virginia, USA
  • Annapolis Junction, Maryland, USA
  • Arlington, Virginia, USA
  • McLean, Virginia, USA
Cyber Machine Learning Engineer

Key Role:  

Build, train, and package production-ready models to detect advanced persistent threats and anomalous or suspicious activity. Implement model performance observability to monitor and mitigate data drift, false positives, and resource utilization. Identify new opportunities for effective applications of machine learning to unique cyber defense use cases. Keep aware of latest research in machine learning and cybersecurity, and demonstrate a history of intellectual curiosity, as the problems we solve require creative solutions. Work on the cutting-edge of production systems for cybersecurity. Contribute to novel and impactful work, using your machine learning and cybersecurity expertise to enable and automate real-time detection and defense against threat actors, for both federal and commercial clients. 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. Build your experience in cyber defense and machine learning, while developing models and software that will defend the nation.

Basic Qualifications:  

  • 2+ years of experience with cyber threat hunting and analysis of compromises within security telemetry such as endpoint and network data 
  • 2+ years of experience training and monitoring machine learning models for use with batch data and streaming data 
  • Experience using Python
  • Experience with MLOps practices, including CI/CD 
  • Experience packaging and deploying production-level models using Docker or Kubernetes 
  • Experience with SIEM technologies such as Splunk or Elastic Stack 
  • Experience with MITRE ATT&CK framework, MISP threat sharing, or cyber intelligence platforms 
  • Experience with cloud platforms such as AWS or Azure 
  • Ability to obtain a Secret clearance
  • Bachelor’s degree 

Additional Qualifications:   

  • Experience with data engineering, including ETL pipelines and platforms such as Databricks 
  • Experience working with large language models (LLMs) 
  • Experience with agentic AI solutions and associated techniques and tools such as RAG 
  • Experience with AWS GovCloud 
  • Experience with Zero Trust security principles 
  • Experience with message brokers or streaming platforms such as Kafka, Amazon Kinesis, RedPanda, or RabbitMQ 
  • Possession of excellent problem-solving skills
  • Secret clearance
  • Master’s degree preferred; Doctorate degree a plus 

Clearance:  

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.

Compensation

At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date.

Identity Statement

As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Work Model
Our people-first culture prioritizes the benefits of flexibility and collaboration, whether that happens in person or remotely.

  • If this position is listed as remote or hybrid, you’ll periodically work from a Booz Allen or client site facility.
  • If this position is listed as onsite, you’ll work with colleagues and clients in person, as needed for the specific role.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.

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