Modern Government Solutions

Modern Government Solutions

Senior AI/ML Engineer

Dana Point, California, USA · Senior · Full-time

No sponsorship$53k-$800kDetected 28 days ago
TypeScriptPythonDatabricksAWSAzureDockerKubernetesMachine LearningTensorFlowPyTorchscikit-learnSparkData EngineeringData ScienceData VisualizationRAGMLOpsCybersecurityCommunicationProblem SolvingPipeline IntegrityCompTIA

About the role

  • This position sits at the intersection of AI engineering, data infrastructure, and operational execution, ensuring capabilities are not only developed but successfully deployed and used in the field.
  • Stay current on emerging AI/ML technologies, DoD AI initiatives, and secure cloud capabilities to inform solution development and program strategy.

Responsibilities

  • Design, develop, and deploy AI/ML models supporting telemetry analysis, automated collection planning, anomaly detection, predictive maintenance, and decision-aid tools for RDT&E events.
  • Architect and implement end-to-end ML and data pipelines in Azure Government (AzureGov), including data ingest/ETL, labeling workflows, governance, and role-based access controls for experiment data.
  • Develop AI-enabled applications and automation solutions within MS365 GCC High and Azure environments, including intelligent document processing, workforce analytics, predictive staffing models, and natural language interfaces.
  • Implement advanced AI capabilities such as Retrieval-Augmented Generation (RAG), knowledge management solutions, and data visualization products (dashboards, COP views) to support operational decision-making and Government evaluations.
  • Establish MLOps practices, including model versioning, experiment tracking, reproducibility, and lifecycle management to support RDT&E repeatability and transition decisions.
  • Develop and maintain technical documentation, data/model traceability, and performance artifacts to support engineering requirements, Government reviews, and program deliverables.
  • Operate across office and laboratory environments, providing hands-on support to users and operational systems supporting AI/ML capabilities.
  • Support test events and operational activities as needed, including extended hours and up to 20% travel to meet program and mission requirements.
  • Proven experience designing, building, and deploying production AI/ML systems, including models, pipelines, and end-to-end data workflows.
  • Demonstrated experience developing AI/ML solutions in Azure Government or equivalent FedRAMP High cloud environments.

Requirements

  • Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, Hugging Face).
  • Hands-on experience with data pipeline engineering (e.g., Apache Spark, Azure Data Factory, Databricks) and large-scale data processing.
  • Experience with MLOps practices, including model versioning, experiment tracking, reproducibility, and containerized deployment (Docker, Kubernetes).
  • Familiarity with Azure AI/ML services (Azure ML, Azure OpenAI, Cognitive Services) and development within MS365 GCC High environments.
  • Experience working within cybersecurity and compliance frameworks (CMMC 2.0, NIST SP 800-53) and handling controlled data (PII/CUI).
  • Strong understanding of data governance, access controls, and secure data handling in classified or controlled environments.
  • REQUIRED SKILLS AND QUALIFICATIONS Must possess an active Department of Defense (DoD) Secret security clearance.

Compensation

  • $53k-$800k

Benefits

  • Bachelor's degree in Computer Science, Data Science, Machine Learning, Mathematics, or related field.
  • 8+ years of experience in AI/ML engineering, data science, or applied machine learning, with experience supporting DoD or Federal environments.
  • Master's degree in Computer Science, Data Science, Machine Learning, Mathematics, or related field.

Visa & Work Authorization

  • REQUIRED SKILLS AND QUALIFICATIONS Must possess an active Department of Defense (DoD) Secret security clearance
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This listing is sourced directly from Modern Government Solutions's careers page and normalized into a canonical job model.