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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** CACI International Inc. - **Location:** San Antonio, TX, United States - **Experience:** Experienced - **Salary:** $93,500.0 - $196,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Artificial Neural Networks, Confluence, JIRA, Apache Lucene, Computer Programming, Computer Networks, Data Cleansing, Elasticsearch, Python (Programming Language), Network Security, Machine Learning, NumPy, Systems Development Life Cycle, Tensorflow, Software Construction, Feature Engineering, Pytorch, Grafana, Deep Learning, Keras, Git, Pandas, Matplotlib, Spark Mllib, Scikit Learn, Kubernetes, Low Latency, HuggingFace, Cybercrime, Xgboost, Apache Kafka, Apache Nifi, Machine Learning Operations, Kibana, Data Pipelines, Docker, Elk Stack, Unsupervised Learning - **Published:** August 16, 2026 - **Apply:** https://www.juju.com/job/00000000gnag86 ## About the Role _Required:_ + **Clearance:** Active TS/SCI security clearance. + **Certification:** DOD Directive 8140.01 (Security+ or equivalent must be obtained within 6 months of hire). + **Experience:** 5+ years in Machine Learning focused on deploying models into production. + **Education:** Master's in Data Science, AI, or related quantitative field preferred. + **Technical Skills:** Deep knowledge of ML frameworks such as PyTorch or TensorFlow. + **Programming:** Strong Python. ML libraries including Spark MLlib, Scikit-learn, XGBoost, Keras, Hugging Face, PyTorch Geometric, MLflow. Explainability tools such as SHAP, GNNExplainer, or attention-based interpretation methods. + **Data:** Extensive experience incorporating data from multiple sources, labeling data for training, and identifying hidden patterns. + **Visualization:** Matplotlib, Grafana, or Kibana. Communication: Ability to communicate complex problems and solutions to non-technical leadership. Desired: + 2+ years developing analytic solutions at scale over multiple PB of data. + Experience with: + Elasticsearch (ELK stack) and Lucene. + Docker/Kubernetes and containerized products. + CI/CD pipelines and Git. + Data pipelines - Pandas, NumPy, NiFi, Kafka, or similar. + Confluence, Jira, and collaborative platform experience. + Software engineering best practices across the full development lifecycle. + Familiarity with network defense, cybersecurity principles, and threat hunting. + Familiarity with data collection, storage, and monitoring. ## Description The 35th Intelligence Squadron seeks a motivated AI/ML Engineer to develop and deploy complex Artificial Intelligence systems defending the Department of Defense Air Force Information Network (AFIN). The role requires anomaly detection algorithms for identifying and isolating malicious threats using supervised and unsupervised learning, Graph Neural Networks, and Deep Learning models. You will drive our cyber threat intelligence and detection mission by providing expert leadership and mentorship in advanced AI/ML solutions, augmenting cyber threat analysts triaging 1TB+ of boundary device logs daily to produce defensible intelligence reports with real mission consequences. You will provide technical direction for the design, implementation, testing, deployment, and operation of the 35 IS's cyber threat detection methods and enabling systems. Responsibilities: + **Design & Deplo** y: Architect, build, and deploy high-performance ML models with 1TB+ daily ingestion across heterogeneous data sources into production, ensuring scalability, reliability, and low latency. + **Drive the ML Lifecycle** : Lead data preparation, model development, evaluation, monitoring, drift detection, and continuous retraining within mission-aligned constraints. + **Model Innovation:** Develop and implement state-of-the-art algorithms, specifically a hybrid GNN and BiLSTM architecture operating on a continuously updated heterogeneous network graph. + **Optimize:** Improve model performance through feature engineering, hyperparameter tuning, and advanced experimentation. + **Mentorship** : Mentor junior software developers and provide technical guidance and expertise. + **Logistics** : Ensure appropriate documentation for all delivered analytics. Build explainability into the product from the beginning to support defensible intelligence reports. Ensure analyst trust is a design requirement, not an afterthought. ## Related Videos - [Industrializing your Data Science capabilities](https://www.wearedevelopers.com/videos/178-industrializing-your-data-science-capabilities) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Improving quality with Agentic AI with Rovo Dev and Xray](https://www.wearedevelopers.com/videos/2005-improving-quality-with-agentic-ai-with-rovo-dev-and-xray) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Overview of Machine Learning in Python](https://www.wearedevelopers.com/videos/840-overview-of-machine-learning-in-python) - [Collaboration Quantified: Lessons from Open Source Developer Networks](https://www.wearedevelopers.com/videos/1422-collaboration-quantified-lessons-from-open-source-developer-networks) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)