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As an experienced engineer, you understand that modern mission systems depend on the ability to develop, optimize, and deploy AI/ML models that can operate reliably at scale. Your expertise in analyzing datasets, engineering features, and applying advanced statistical and machine learning techniques will be critical to ensuring model readiness and enhancing real-world operational outcomes. We need your technical depth and problem-solving mindset to advance the development, deployment, and continuous improvement of AI models that directly support evolving mission needs.
Job Responsibility
Design, test, optimize, and operationalize models across cloud, edge, and hybrid environments
Drive technical direction for mission-critical AI solutions by selecting best-fit architectures, implementing robust deployment pipelines, and integrating models with enterprise and mission systems
Collaborate closely with data engineers, data scientists, cloud and network architects, and ISSE partners
Contribute technical leadership by evaluating emerging AI/ML frameworks, guiding feature engineering approaches, supporting fine-tuning and retraining cycles, and implementing monitoring frameworks to detect performance drift
Help mission partners understand and navigate the evolving landscape of AI/ML technologies
Requirements
6+ years of experience with engineering
Experience developing, training, validating, and deploying AI/ML models across cloud, edge, or hybrid environments
Experience with data preprocessing, feature engineering, and exploratory data analysis
Experience optimizing AI/ML models including compression, pruning, quantization, and distributed training
Experience with computing, storage, and networking requirements across model training, tuning, and inference phases
Knowledge of statistical modeling, machine learning workflows, and model evaluation techniques
Ability to design and implement model deployment pipelines and MLOps workflows
Ability to implement monitoring frameworks for detecting model drift, performance degradation, and operational issues
TS/SCI clearance with a polygraph
HS diploma or GED
Nice to have
Experience with distributed compute frameworks such as Ray, Spark, or Horovod for large-scale model training
Experience with cloud-native AI platforms including AWS Sagemaker, Azure ML, or GCP Vertex AI
Experience deploying AI/ML models to edge devices or tactical and operational environments
Experience with common ML frameworks such as PyTorch, TensorFlow, or Scikit-learn
Experience working in mission-focused or national security environments
Experience with vector databases, data lakehouse architectures, or streaming data systems
Experience evaluating new AI model architectures such as LLMs or diffusion models and conducting model benchmarking
Knowledge of secure AI engineering best practices such as adversarial robustness, model governance, or NIST AI RMF
Possession of strong programming skills in languages such as Python
Bachelor's degree
What we offer
Health, life, disability, financial, and retirement benefits