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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Engineer - **Company:** Quantum Science Solutions - **Location:** Arlington, VA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Big Data, Cloud Engineering, Computer Programming, Computer Engineering, System Configuration, Data Architecture, Data Cleansing, Information Engineering, Data Integration, Data Transformation, Data Security, Apache Hadoop, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Azure Machine Learning, Software Engineering, Data Streaming, Systems Integration, Workflow Management Systems, Software Repository, Data Processing, Feature Engineering, Large Language Models, Apache Spark, Software Security, Malware, Cyber Threat Analysis, Git, SC Clearance, Containerization, AI Platforms, Kubernetes, Information Technology, Cybercrime, Enterprise Integration, Apache Kafka, Non-relational Database, Machine Learning Operations, Cloud Migration, Restful APIs, Cyber Warfare, Software Version Control, Data Pipelines, Api Management, Docker, Unified Endpoint Management, Databricks - **Published:** June 30, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9004199/aiml-engineer ## About the Role * U.S. Citizenship. * Active Secret Clearance (TS/SCI Preferred). * Ability to obtain DHS Suitability. * Minimum of 5+ years of experience in automation engineering, software engineering, data engineering, or related technical disciplines. * Experience designing and implementing data ingestion pipelines within AWS cloud environments. * Experience configuring, tuning, deploying, and integrating Artificial Intelligence (AI) and Large Language Models (LLMs). * Experience designing, implementing, and maintaining Machine Learning (ML) pipelines. * Strong programming skills in Python, including experience with data manipulation and automation libraries. * Experience utilizing Amazon Bedrock, including model access, endpoint configuration, and API integration. * Experience with automation frameworks, workflow orchestration platforms, and integration technologies. * Experience developing and consuming RESTful APIs and enterprise integrations. * Understanding of relational and non-relational databases, data modeling, and data architecture principles. * Experience utilizing Git-based version control systems and CI/CD development practices. * Strong analytical, troubleshooting, and problem-solving skills. * Ability to translate business and mission requirements into scalable automation solutions. * Excellent written and verbal communication skills with experience producing technical documentation. Preferred Skills * Experience developing automation for malware analysis, cyber defense, or threat intelligence operations. * Knowledge of AI/ML data preparation, feature engineering, and model lifecycle management. * Experience with Databricks and Databricks AI platforms. * Experience using workflow orchestration technologies such as: Apache Airflow and Prefect. * Background supporting cybersecurity operations, threat hunting, or cyber threat intelligence programs. * Experience with containerization and orchestration technologies including: Docker and Kubernetes. * Knowledge of streaming data platforms such as: Apache Kafka and Amazon Kinesis. * Experience working with big data technologies including: Apache Spark and Hadoop. * Experience supporting Federal cybersecurity, cloud modernization, or AI initiatives. * Familiarity with MLOps, cloud-native application development, and scalable AI deployment architectures., * Bachelor's degree in Computer Science, Data Science, Software Engineering, Artificial Intelligence, Machine Learning, Computer Engineering, or a related technical discipline. OR * High School Diploma with 7-9 years of High School Diploma with 7+ years of directly relevant experience in AI/ML engineering, automation engineering, software development, or data engineering. Desired Certifications * DoD 8140 IAT Level III * Certified Secure Software Lifecycle Professional (CSSLP) * AWS Certified Machine Learning - Specialty * AWS Certified Developer - Associate * AWS Certified Solutions Architect - Associate * Microsoft Azure AI Engineer Associate * Databricks Certified Machine Learning Professional * TensorFlow Developer Certification * Certified Kubernetes Application Developer (CKAD) ## Description Quantum Science Solutions (QSS) is seeking an innovative AI/ML Engineer to support mission-critical cybersecurity operations for Federal agencies and critical infrastructure organizations. This position focuses on designing and implementing intelligent automation solutions that accelerate machine learning technology integration, streamline cyber operations, and enhance incident response capabilities. The selected candidate will develop scalable AI/ML workflows, automated data pipelines, and cloud-native integration solutions that support malware analysis, threat intelligence, and advanced analytics. Working closely with cybersecurity analysts, software engineers, data engineers, and cloud architects, the AI/ML Engineer will transform manual processes into intelligent, automated capabilities that improve operational efficiency and enable rapid deployment of emerging technologies., * Design, develop, and maintain automated data pipelines supporting AI/ML technology integration initiatives. * Build intelligent workflows for malware sample collection, detonation, classification, and taxonomy management. * Develop and integrate AI and Large Language Model (LLM) capabilities using Amazon Bedrock, Databricks, and other cloud-based AI platforms. * Implement automated data integration processes between pilot environments and production systems. * Support the development, enhancement, and sustainment of Automated Malware Analysis (AMA) platforms. * Develop scripts, utilities, and automation tools that eliminate repetitive technical tasks and improve operational efficiency. * Design and implement automated data transformation, normalization, and feature engineering processes. * Develop AI/ML pipelines that support model training, validation, deployment, and continuous improvement. * Create monitoring, alerting, and health-check automation for AI/ML platforms and integrated systems. * Design and implement API integrations to enable secure data sharing and workflow automation across enterprise systems. * Optimize automation solutions for scalability, performance, reliability, and maintainability. * Maintain code repositories, technical documentation, deployment guides, and automation workflows. * Support the transition of AI/ML solutions from pilot implementations into production environments. * Collaborate with cybersecurity analysts and mission stakeholders to identify automation opportunities and improve operational workflows. * Ensure automation solutions maintain data quality, integrity, and compliance with organizational standards. * Participate in continuous improvement initiatives to enhance AI/ML capabilities, automation frameworks, and cloud-native architectures. ## Related Videos - [Architecting the Future: Leveraging AI, Cloud, and Data for Business Success](https://www.wearedevelopers.com/videos/1096-architecting-the-future-leveraging-ai-cloud-and-data-for-business-success) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [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) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? 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