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Software Engineer w/ Cloud - TS/SCI w/poly
Optimize governance, risk, and compliance processes using AI-driven predictive analytics and real-time monitoring tailored for global financial institutions.
Benefits:
Fully paid medical/dental/vision premiums
Generous PTO
11 Paid Holidays
6% 401K contribution
Annual training and tuition reimbursement
Experience Requirements:
Experience leveraging background in programming and Software tools
Python
Cloud services (Lambda, S3, Batch, EC2, EventBridge, SQS/SNS, IAM, DynamoDB, containers)
AWS CDK
Building and maintaining secure web applications on JWICS C2S network
Other Requirements:
Active TS/SCI w/ FS Poly required
Experience in System Administration preferred
Linux shell scripting experience preferred
Responsibilities:
Rapidly develop and operate new techniques for data collection and transformation
Co-locate with end-users to solve collection needs
Prioritize work based on mission need
Document and communicate technical mission requirements
Work with other technical teams across multiple organizational boundaries
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Senior Machine Learning Engineer – Agentic AI Systems (TS/SCI)
Automate reverse engineering and binary analysis using AI-powered static and dynamic tools with Model Context Protocol integration for existing security agents.
Experience Requirements:
4+ years building ML solutions at scale
Strong Python; deep experience with PyTorch/TensorFlow
Hands-on distributed systems experience (Ray highly valued)
Understanding of LLM orchestration, memory, retrieval, and planning
Experience with MLOps/model versioning and experiment tracking (e.g., MLflow, DVC, Weights & Biases)
Other Requirements:
Active TS/SCI clearance
Builder's mindset
Experience working with cyber/network telemetry or security datasets is a plus
Familiarity with model security/adversarial ML
Ability to identify and mitigate vulnerabilities
Responsibilities:
Architect, train, and deploy AI systems for reasoning, planning, and multi‑step decision‑making
Build and scale distributed training/inference pipelines using Ray and modern cloud infrastructure
Integrate agentic AI into operational environments across cross‑functional teams
Prototype techniques from memory‑augmented models to tool‑use orchestration
Develop ML models on cyber data to support object detection, data triage, search/optimization, inference, behavior detection, and automated discovery and decision making
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