AI / Machine Learning Engineer

Guidehouse is a consulting firm that focuses on delivering advanced analytics and AI-enabled solutions for federal clients. The AI / ML Engineer will design, build, and deploy scalable machine learning models and data pipelines to support mission-critical decision-making across defense and federal financial domains.

Responsibilities:

• Design, build, train, and deploy machine learning models to support operational, analytical, and decision-support use cases
• Develop and maintain end-to-end ML pipelines, from data ingestion and feature engineering through model training and evaluation
• Apply supervised and unsupervised learning techniques, including classification, regression, clustering, and anomaly detection
• Work with large-scale structured and semi-structured federal datasets, including financial, budgetary, and transactional data
• Engineer solutions in secure cloud and on-prem environments in compliance with DoD and federal security controls
• Collaborate with stakeholders to translate analytic outcomes into actionable insights and mission value
• Contribute to solution documentation, model explainability, and government-facing deliverables
• Support continuous improvement of data science and ML engineering best practices across teams

Requirements:

• US Citizenship is required
• An ACTIVE and MAINTAINED 'SECRET' Federal or DoD security clearance
• Bachelor's degree obtained
• 3–5 years of professional experience in machine learning, AI engineering, data science, or advanced analytics
• Demonstrated experience building and deploying ML models using Python and modern ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow)
• Strong experience with data manipulation and analysis using SQL, Pandas, NumPy, and related tools
• Experience working in secure federal environments, particularly DoD or Intelligence Community programs
• Understanding of model validation, explainability, performance monitoring, and bias considerations
• Ability to communicate complex technical concepts clearly to technical and non-technical audiences
• Experience supporting the Department of Defense, particularly work involving Advana or enterprise DoD data platforms
• Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical field
• Hands-on experience working with federal financial or budgetary data (e.g., audit, accounting, execution, or spend analytics)
• Experience engineering solutions on Databricks (including Spark, MLflow, Delta Lake)
• Experience building analytics or ML solutions using Palantir Foundry
• Familiarity with MLOps practices, CI/CD for ML, and model lifecycle management
• Experience working in cloud environments such as Azure (including GovCloud) or AWS GovCloud
• Master's degree in a related quantitative or technical discipline