AI/ML Engineer – Clearance Required

This is a fully remote position, open to applicants in United States.

📋 Description

• Create, implement, evaluate, and enhance machine learning algorithms for predictive forecasting, rate prediction, resource allocation, and real-time decision-making support.

• Build supervised, unsupervised, time-series, regression, ensemble, NLP, generative AI, large language models, and retrieval-augmented generation solutions.

• Develop reusable model services, APIs, containers, and software components that integrate with secure web applications, dashboards, and mission data products.

• Design scalable architectures for both batch and real-time inference, model serving, monitoring, and application support across development, testing, and production stages.

• Incorporate predictive models into existing web applications and enterprise workflows.

• Collaborate with data scientists and data engineers on data structures, features, pipelines, interfaces, and validation techniques.

• Perform performance testing, hyperparameter tuning, error analysis, back-testing, drift detection, and model monitoring.

• Implement MLOps and DevSecOps methodologies for source control, automated testing, CI/CD, model versioning, deployment, monitoring, rollback, and maintenance.

• Apply responsible and secure AI/ML engineering practices, including access control, data protection, governance, explainability, evaluation, auditability, and risk management.

• Assist in the synchronization, integration, governance, maintenance, and adoption of AI/ML capabilities across mission teams and products.

• Develop automation and augmentation initiatives to reduce human cognitive workload and address emerging operational needs.

• Create technical documentation that encompasses algorithms, architecture, interfaces, security, testing, deployment, operations, and integration.

• Generate user manuals, training materials, demonstrations, instructional videos, and knowledge-transfer products.

• Provide rapid-response engineering and product-level staff augmentation aligned with mission priorities.

⛳️ Requirements

• Active Secret security clearance with the capability to acquire a Top Secret clearance.

• Bachelor’s degree in computer science, artificial intelligence, machine learning, data science, software engineering, mathematics, engineering, or a related technical discipline.

• A minimum of five years of professional experience in designing, developing, deploying, and maintaining machine learning models or AI-enabled software capabilities in production settings.

• Advanced skills in Python and practical experience with contemporary machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost, or similar technologies.

• Proven experience in developing and validating predictive models, including time-series, regression, ensemble, or similar forecasting methodologies.

• Experience in operationalizing models via APIs, services, containers, automated testing, version control, CI/CD, model registries, monitoring, and repeatable deployment processes.

• Familiarity with SQL, data structures, feature pipelines, data quality controls, and secure integration with relational, non-relational, object-storage, or analytical data platforms.

• Experience in designing scalable architectures for batch or real-time inference, model serving, application integration, monitoring, and production support.

• Knowledge of responsible and secure AI/ML engineering practices, including access control, data protection, model governance, explainability, evaluation, auditability, and risk management.

• Experience in producing clear documentation on algorithms, architecture, interfaces, testing, deployment, operations, and knowledge transfer.

• Strong written and verbal communication skills with the ability to collaborate across data science, data engineering, software, cybersecurity, governance, and operational teams.

• Capability to independently prioritize multiple tasks and deliver consistent production capabilities in a dynamic, mission-driven environment.

• Preferred: Master’s degree; experience with secure government cloud environments such as AWS GovCloud or Azure Government; knowledge of Kubernetes; infrastructure as code; DevSecOps; prior military service or direct professional experience supporting U.S. Special Operations Forces.

🏝️ Benefits

• Competitive salary and performance-based incentives.

• Comprehensive health, dental, and vision insurance.

• Generous retirement plan options.

• Flexible work hours and remote work opportunities.

• Professional development and training programs.

• Collaborative and innovative work environment.