AI/ML Engineer

Booz Allen Hamilton•Usa, DC

1d•Remote

About The Position

As an experienced engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using AI and ML techniques makes you an integral part of delivering a customer-focused solution. We need your technical knowledge and desire to problem-solve to support the advancement of AI and ML within our National Resiliency Account. As a machine learning engineer on our National Resiliency team, you’ll train, test, deploy, and maintain models that learn from data. In this role, you’ll own and define the direction of mission-critical solutions by applying best-fit AI and ML algorithms and technologies. You’ll be part of a talented team of artificial intelligence and machine learning engineers across the company and collaborate with business and technical leaders to deliver world-class AI and ML solutions that solve our nation’s toughest and hardest problems. Your skills and extensive technical expertise will guide clients as they navigate the landscape of AI and ML algorithms, tools, and frameworks.

Requirements

5+ years of experience designing and delivering production ML systems
2+ years of experience on U.S. federal government programs
Experience in Python such as scikit-learn, XGBoost, PyTorch, TensorFlow, PySpark, or SQL
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
Bachelor's degree

Nice To Haves

Experience with Databricks Lakehouse Platform
Experience operating within FedRAMP-authorized cloud environments
Experience with Terraform, CloudFormation, and CI / CD pipelines, such as GitLab CI or AWS CodePipeline
Experience with federal or government technology, data, and model standard such as CMMC or RMF
Experience with prompt engineering and RAG architecture a plus
Knowledge of large language model (LLM) deployment patterns in air-gapped or restricted network environments
Public Trust
Master's degree
AWS Machine Learning Specialty, Databricks Certified Machine Learning Professional, or vendor Certification

Responsibilities

Design, develop, validate, and deploy supervised and unsupervised AI / ML models.
Implement MLOps pipelines on AWS GovCloud using SageMaker, Step Functions, and Databricks ML Runtime.
Build and maintain PySpark and Delta Lake pipelines within a medallion architecture.
Develop feature stores aligned to Unity Catalog governance standards.
Perform data profiling and quality validation consistent with government data standards.
Ensure all AI / ML artifacts comply with Executive Order 14110 AI safety requirements and applicable NIST AI RMF guidance.
Maintain model cards, bias assessments, and explainability documentation for all production models.
Support Authority to Operate (ATO) activities, including AI-specific control documentation under NIST SP 800-53 Rev 5.
Implement model monitoring frameworks for concept drift, data drift, and performance degradation.
Produce monthly model performance reports in accordance with COR-approved formats.
Maintain retraining cadences and version control using MLflow within Databricks Workspace.
Collaborate with program offices, IRS, and partner agencies to translate mission requirements into model specifications.
Brief government counterparts at the GS-14, GS-15, and SES level on model performance, risk, and roadmap.
Produce artifacts suitable for a detailed government review.