AI and ML Engineer, Mid

About the role

The AI and ML Engineer, Mid position involves designing, building, and implementing practical AI/ML capabilities that enhance mission systems and support faster, more informed decision-making across the national security ecosystem. You will contribute across the development lifecycle supporting data processing, model creation, MLOps workflows, and the integration of scalable AI solutions into operational environments while working closely with senior engineers and mission partners.

Responsibilities

• Develop and implement AI-engineered signal-processing and automation tools and capabilities for EO/IR applications.
• Collaborate with multidisciplinary teams to design, develop, test, and deploy technical solutions in support of modernizing analysis workflows.
• Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of applications and processes.
• Contribute to the architecture and implementation of novel approaches for rapidly fielding capabilities, including using streaming data sets and NRT feeds.

Requirements

• Experience developing AI/ML capabilities to operate in a microservice stack.
• Experience devising AI-agent planning, reasoning, and execution loops.
• Experience with Python-based ML frameworks such as PyTorch or TensorFlow.
• Demonstrated experience with statically-sound model evaluation and AI quality metrics.
• Experience building, deploying, and operating production ML models using either supervised, unsupervised, or anomaly detection efforts.

Qualifications

• Active TS/SCI clearance; willingness to take a polygraph exam.
• Bachelor's degree in a STEM field.

Skills

• Experience in GPU programming, including CUDA or RAPIDs.
• Experience with AWS and containerization of models in a classified environment.
• Experience with ML engineering and MLOps, including model versioning, CI/CD for ML, monitoring, drift detection, and automated retraining.
• Knowledge of modern software design patterns, including micro-service design and orchestration in Kubernetes deployment.
• Master’s degree in CS, AI, or Data Science.

Benefits

Nice if you have:

• Experience in GPU programming, including CUDA or RAPIDs.
• Experience with AWS and containerization of models in a classified environment.
• Experience with ML engineering and MLOps, including model versioning, CI/CD for ML, monitoring, drift detection, and automated retraining.
• Knowledge of modern software design patterns, including micro-service design and orchestration in Kubernetes deployment.
• Master’s degree in CS, AI, or Data Science.

Pay

$77,500.00 to $176,000.00 (annualized USD)

Schedule

Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits.