Artificial Intelligence/Machine Learning Engineer, Senior

Responsibilities

• Work directly with mission users to develop and deploy AI and ML solutions enhancing operational workflows.
• Collaborate with operators, analysts, software developers, and mission leadership to capture operational needs and translate them into effective AI-enabled capabilities.
• Develop LLM-powered workflows, agent-based automation, and other AI/ML solutions to streamline analytical tasks and improve mission effectiveness.
• Support the integration of AI capabilities into existing operational systems while ensuring solutions are reliable, scalable, and compliant with security and governance requirements in classified environments.
• Contribute to data pipeline development, model evaluation, workflow optimization, and operational testing to support production-ready AI solutions.

Qualifications

• Experience with architecting and delivering enterprise-scale AI/ML solutions in professional or mission-oriented environments.
• Experience with large language models (LLMs), generative AI systems, and agentic AI development, including production deployment.
• Experience with designing and implementing end-to-end machine learning pipelines, including data engineering, model training, evaluation, deployment, and monitoring.
• Expert-level ability in Python for AI/ML development, data engineering, and pipeline construction.
• Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders.
• TS/SCI clearance with a Polygraph.
• Bachelor's degree in Computer Science, Data Science, Electrical Engineering, Mathematics, Statistics, or a related technical field with 10+ years of relevant experience; Master's degree with 7+ years; or PhD with 4+ years of relevant AI/ML or data science experience.

Nice If You Have

• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Experience with cloud platforms such as AWS, Azure, or GCP, as well as distributed computing frameworks.
• Experience with containerization and orchestration tools such as Docker and Kubernetes.
• Experience with designing and implementing MLOps platforms, including end-to-end model lifecycle management and automated retraining systems.
• Experience with natural language processing (NLP) techniques, including topic modeling, text classification, named entity recognition, and semantic/vector search.
• Experience with multi-modal data processing across text, imagery, speech, and video modalities.
• Experience with contributing to technical proposals, RFP responses, and government white papers.
• Experience with supporting DoD or Intelligence Community programs.
• Knowledge of agentic AI frameworks, multi-agent architectures, and intelligent orchestration patterns.
• Knowledge of security requirements and compliance frameworks for AI/ML systems operating in government environments.

Compensation

The projected compensation range for this position is $108.17 to $146.63 per hour.