AI/ML Engineer

Booz Allen Hamilton•Washington, DC

1d•$99,000 - $225,000•Remote

About The Position

As an experienced engineer, you know that machine learning (ML) is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using AI/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 an ML 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/ML algorithms and technologies. You’ll be part of a talented team of AI and ML engineers across the company and collaborate with business and technical leaders to deliver world-class AI/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/ML algorithms, tools, and frameworks.

Requirements

2+ years of experience on U.S. federal government programs
1+ years of experience designing and delivering production on ML systems
Experience in Python such as scikit-learn, XGBoost, PyTorch, or TensorFlow, PySpark, and SQL
Ability to travel up to 25% of the time
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
Bachelor's degree in a CS, Data Science, Statistics, or Applied Mathematics field

Nice To Haves

Experience with the 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 standards such as CMMC or RMF
Experience with prompt engineering and RAG architecture
Knowledge of large language model (LLM) deployment patterns in air-gapped or restricted network environments
Public Trust
Master’s degree
AWS ML Specialty, Databricks Certified ML Professional, or equivalent 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, the IRS, and partner agencies to translate mission requirements into model specifications.
Brief government counterparts at the GS-14 or 15 and SES level on model performance, risk, and roadmaps.
Produce artifacts suitable for a detailed government review.