AI Model SME

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 problemsolving mindset to advance the development, deployment, and continuous improvement of AI models that directly support evolving mission needs.

As an AI Model SME on our team, you'll design, test, optimize, and operationalize models across cloud, edge, and hybrid environments. You will drive the technical direction for missioncritical AI solutions by selecting bestfit architectures, implementing robust deployment pipelines, and integrating models with enterprise and mission systems. You'll collaborate closely with data engineers, data scientists, cloud and network architects, and ISSE partners to ensure models are supported by secure, scalable infrastructure and highquality data pipelines. You'll also contribute technical leadership by evaluating emerging AI/ML frameworks, guiding feature engineering approaches, supporting finetuning and retraining cycles, and implementing monitoring frameworks to detect performance drift.

Your expertise will help mission partners understand and navigate the rapidly evolving landscape of AI/ML technologies, ensuring deployed models remain performant, reliable, and aligned with operational objectives. Work with us to solve complex realworld challenges and shape the model lifecycle strategy that will drive innovation across mission environments.

Join us. The world can't wait.

You Have:

• 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 If You 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

Clearance:

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance with polygraph is required.