AI/ML Engineer - Clearance Required
Logistics Management Institute17 days ago
Remote, United StatesSenior
Base Salary
$122k - $211k/yr
Responsibilities
- Design, implement, test, optimize, and validate machine-learning algorithms and predictive models for forecasting, rate prediction, resource planning, and real-time decision support.
- Develop NLP and generative-AI solutions, including large language models and retrieval-augmented generation capabilities.
- Engineer reusable model services, APIs, containers, and software components for secure web applications, dashboards, and mission data products.
- Design scalable architectures for batch and real-time inference, model serving, monitoring, application integration, and production support.
- Collaborate with data scientists and data engineers on data structures, features, pipelines, interfaces, validation, training, evaluation, deployment, and sustainment.
- Implement MLOps and DevSecOps practices covering source control, automated testing, continuous integration and delivery, model versioning, deployment, monitoring, rollback, and sustainment.
- Apply responsible and secure AI/ML practices involving access control, data protection, governance, explainability, evaluation, auditability, and risk management.
- Produce and maintain technical documentation, user guides, training materials, demonstrations, instructional videos, and knowledge-transfer materials.
- Provide rapid-response engineering and product-level staff augmentation as mission priorities and operational requirements change.
Requirements
- Active Secret security clearance with the ability to obtain a Top Secret clearance.
- Bachelor’s degree in computer science, artificial intelligence, machine learning, data science, software engineering, mathematics, engineering, or a related technical field.
- Five or more years of professional experience designing, developing, deploying, and sustaining production machine-learning models or AI-enabled software capabilities.
- Advanced Python proficiency and practical experience with modern machine-learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, or XGBoost.
- Experience developing and validating predictive models, including time-series, regression, ensemble, or comparable forecasting methods.
- Experience operationalizing models through APIs, services, containers, automated testing, version control, continuous integration and delivery, model registries, monitoring, and repeatable deployment.
- Working knowledge of SQL, data structures, feature pipelines, data quality controls, and secure integration with relational, non-relational, object-storage, or analytical data platforms.
- Experience designing scalable batch or real-time inference, model-serving, application-integration, monitoring, and production-support architectures.
- Knowledge of responsible and secure AI/ML engineering practices, including access control, data protection, governance, explainability, evaluation, auditability, and risk management.
- Experience producing technical and knowledge-transfer documentation for technical and non-technical stakeholders, plus strong written and verbal communication skills.
- Ability to collaborate across data science, data engineering, software, cybersecurity, governance, and operational teams and independently manage multiple priorities.
- Preferred qualifications include a master’s degree, experience with AWS GovCloud or Azure Government, Kubernetes, infrastructure as code, or DevSecOps, and prior military or U.S. Special Operations Forces support experience.
Benefits
- Remote position in the United States.
- The role supports a SOCOM mission partner and requires an active Secret clearance with the ability to obtain Top Secret clearance.
Tech Stack
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