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# AI/ML Engineer - Remote

- **Company:** Washington and Idaho Railway Inc
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $122,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automation of Tests, Continuous Integration, Data Structures, Decision Support Systems, Monitoring of Systems, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Standard Sql, Web Application Security, Software Engineering, Management of Software Versions, Performance Testing, Pytorch, Deep Learning, Generative AI, Scikit Learn, Real-time Inference, Information Technology, Xgboost, Enterprise Integration, Data Management, Machine Learning Operations, Software Version Control, Data Pipelines, Devsecops
- **Published:** October 7, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pplemkxax4

## About the Role

* 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 in designing, developing, deploying, and maintaining machine learning models or AI-enabled software in production environments
 * Proficiency in Python and experience with frameworks such as PyTorch, TensorFlow, scikit-learn, XGBoost, or similar
 * Experience developing and validating predictive models, including time-series, regression, ensemble, or forecasting methods
 * Operational experience with APIs, containers, automated testing, version control, CI/CD pipelines, and model monitoring
 * Knowledge of SQL, data structures, feature pipelines, and secure integration with various data platforms
 * Understanding of scalable architectures for batch and real-time inference, model serving, and production support
 * Familiarity with responsible AI/ML practices, including governance, explainability, data protection, and risk management
 * Ability to produce comprehensive technical documentation and collaborate effectively across multidisciplinary teams

## Description

The AI/ML Engineer position at LMI involves supporting a Special Operations Command (SOCOM) mission partner by developing, implementing, and maintaining advanced machine learning and artificial intelligence capabilities. This role requires designing scalable models for predictive forecasting, natural language processing, generative AI, and real-time decision support. The engineer will work within a cross-functional data science team to translate validated models into reliable operational tools, ensuring integration within secure web-based applications and enterprise workflows. The position demands expertise in AI/ML model development, deployment, and sustainment, along with a strong understanding of secure engineering practices, governance, and documentation. The role offers an opportunity to contribute to mission-critical solutions that automate and augment human decision-making in a secure environment, supporting national security objectives., * Design, develop, test, and optimize machine learning algorithms for predictive analytics, resource planning, and decision support

 * Create natural language processing and generative AI solutions tailored to operational and intelligence use cases
 * Engineer reusable model services, APIs, containers, and software components for seamless integration into secure web applications
 * Develop scalable architectures supporting batch and real-time inference, model deployment, monitoring, and support
 * Integrate predictive models into existing enterprise workflows and applications, ensuring security and reliability
 * Collaborate with data scientists and engineers to establish data pipelines, features, validation, and deployment processes
 * Conduct performance testing, hyperparameter tuning, error analysis, and drift detection to ensure model robustness
 * Implement MLOps and DevSecOps practices for versioning, automation, continuous integration, deployment, and monitoring
 * Apply secure AI/ML engineering principles, including governance, explainability, and risk assessment
 * Support enterprise-wide AI/ML adoption, governance, and sustainment efforts across multiple teams and applications
 * Develop technical documentation, user guides, training materials, and knowledge transfer products for operational continuity
 * Provide rapid-response engineering support and staff augmentation to adapt to evolving mission needs