Cyber AI/ML Research Scientist
About The Position
Peraton Labs is seeking a self-motivated Cyber AI/ML Research Scientist with a strong foundation in cybersecurity technologies, computer networks, and AI/ML to help design and deliver next-generation network-based defensive capabilities. This role focuses on the research, prototyping, and evaluation of AI-enabled cyber detection and modeling of cyber phenomena using techniques such as DNNs, transformer-based models, and agentic AI-assisted approaches. You will work with a small team of research scientists to investigate challenging problems, develop novel models and software prototypes, and demonstrate performance through testbed-based evaluation. The ideal candidate thrives in an environment where they can independently drive technical work while communicating results clearly through presentations and written technical documents.
Requirements
- Minimum of MS with 6+ years of experience or PhD with 3+ YoE in Computer Science, Computer Engineering, or closely related field, with exposure to cyber, networks, and machine learning.
- Demonstrated understanding of cyber concepts including TTPs and the cyber lifecycle (e.g., intrusion phases, detection/response considerations)
- Strong networking fundamentals: IP stack, network configuration concepts, routing/switching basics, protocol layering, and network architecture/layout
- Hands-on experience with ML tooling such a PyTorch, TensorFlow, and/or scikit-learn
- Strong software development skills in Python and/or C/C++
- Proficiency with Linux, Git, and Docker
- Excellent oral and written communication skills (technical presentations + well-structured documentation)
- Ability to work independently, manage ambiguity, and deliver tangible outputs in a research environment
- US Citizenship is a requirement for this position
Nice To Haves
- Experience applying ML to cybersecurity or network analytics, such as intrusion detection, anomaly detection, malware/behavioral modeling, or cyber deception/defense concepts
- Experience with network/security telemetry sources
- Direct experience with transformer models, representation learning, or foundation/LLM-adjacent methods applied to cyber workflows
- Familiarity with agentic workflows and safe evaluation approaches
- Knowledge of adversarial ML / robustness, data poisoning considerations, model security, or operational constraints of ML in defensive environments
- History of peer-reviewed publications, patents, open-source contributions, or evidence of research impact
- Experience working within controlled lab/testbed environments
Responsibilities
- Conduct applied research on AI-enabled cyber defense approaches, including detection, modeling, and characterization of cyber behaviors and phenomena
- Design and implement prototypes that operationalize research into usable capabilities
- Develop and evaluate models using deep learning and transformer-based approaches, and explore agentic AI-assisted methods for analysis, workflow automation, and experimentation
- Work with network and cyber data modalities (e.g., flow, packet, host telemetry, logs)
- Build repeatable experiments and conduct rigorous evaluation in controlled testbeds, including performance measurement, ablations, and robustness testing
- Work with teammates to translate customer needs into technical approaches, balancing novelty with feasibility and deployability
- Produce high-quality technical documentation, briefings and presentations, and contribute to reports, proposals, whitepapers, and publications
- Maintain strong system hygiene: Linux-based development, version control, containers, reproducibility, and clean software practices
- Learn and integrate new tools/technologies quickly to keep pace with evolving customer needs and emerging research
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
