AI/ML Engineer – Clearance Required

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $122k - $211k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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LMI

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1961

📦 Logistics

🏥 Healthcare

🎖️ Defense

Logistics • Healthcare • Defense

LMI is a forward-thinking company that focuses on reimagining the path from insight to outcome through innovative solutions in various sectors, including applied AI and digital health. They provide advanced analytics, engineering support, and performance optimization across defense, health, and civilian markets, with a strong commitment to enhancing mission effectiveness for government clients. With a focus on collaboration and research, LMI aims to drive positive change through its diverse capabilities and partnerships.

📋 Description

• Design, implement, test, and optimize machine learning algorithms for predictive forecasting, rate prediction, resource planning, and real-time decision support • Develop supervised, unsupervised, time-series, regression, ensemble, NLP, generative AI, large language model, and retrieval-augmented generation solutions • Engineer reusable model services, APIs, containers, and software components integrating with secure web applications, dashboards, and mission data products • Design scalable architectures for batch and real-time inference, model serving, monitoring, and application support across development, test, and production • Integrate predictive models into existing web applications and enterprise workflows • Collaborate with data scientists and data engineers on data structures, features, pipelines, interfaces, and validation methods • Conduct performance testing, hyperparameter tuning, error analysis, back-testing, drift detection, and model monitoring • Implement MLOps and DevSecOps practices for source control, automated testing, CI/CD, model versioning, deployment, monitoring, rollback, and sustainment • Apply responsible and secure AI/ML engineering practices, including access control, data protection, governance, explainability, evaluation, auditability, and risk management • Support synchronization, integration, governance, sustainment, and adoption of AI/ML capabilities across mission teams and products • Develop automation and augmentation projects for human cognitive workload and emerging operational requirements • Produce technical documentation covering algorithms, architecture, interfaces, security, testing, deployment, operations, and integration • Develop user guides, training materials, demonstrations, instructional videos, and knowledge-transfer products • Provide rapid-response engineering and product-level staff augmentation based on mission priorities

🎯 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 machine learning models or AI-enabled software capabilities in production environments • Advanced proficiency with Python and practical experience with modern machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost, or comparable technologies • Demonstrated 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, CI/CD, model registries, monitoring, and repeatable deployment processes • 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 developing 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 producing clear algorithm, architecture, interface, test, deployment, operational, and knowledge-transfer documentation • Strong written and verbal communication skills and ability to collaborate across data science, data engineering, software, cybersecurity, governance, and operational teams • Ability to independently manage multiple priorities and deliver reliable production capabilities in a fast-paced, mission-focused environment • Preferred: Master’s degree; secure government cloud environments such as AWS GovCloud or Azure Government; Kubernetes; infrastructure as code; DevSecOps; prior military service or direct professional experience supporting U.S. Special Operations Forces