AI/ML Engineer

Trilogy Federal seeks an experienced Artificial Intelligence and Machine Learning (AI/ML) Engineer to support the Department of Veterans Affairs (VA) Summit Advanced Tooling, Lakehouse, and Artificial Intelligence Services (Summit ATLAS) program. The AI/ML Engineer will design, deploy, and support scalable AI/ML capabilities that enable VA customers to develop, operationalize, and manage advanced analytics and intelligent applications within the Summit Data Platform.

This position will lead the technical implementation of enterprise AI/ML tooling, reusable development frameworks, and production deployment capabilities. The AI/ML Engineer will work with VA stakeholders, data engineers, and technical teams to deliver secure, reliable, and responsible AI/ML solutions that meet Government-approved operational, security, and governance requirements.

Please note, this position is contingent upon award (anticipated early 2027).This role will also require 1-2 domestic business trips per year.

Primary Responsibilities:

• Design, implement, and maintain enterprise AI/ML development and deployment capabilities using Azure Machine Learning, Azure Databricks, Azure AI services, and related technologies.
• Develop and maintain reusable AI/ML solution templates, development environments, and deployment patterns that support predictive analytics, natural language processing, and generative AI applications.
• Build and optimize machine learning pipelines for data preparation, model training, evaluation, deployment, and ongoing performance monitoring.
• Implement Machine Learning Operations (MLOps) practices, including model versioning, registry management, automated testing, deployment workflows, and reproducibility.
• Support the integration of AI/ML models and services with Summit data assets, enterprise applications, and approved cloud infrastructure.
• Implement Government-approved responsible AI controls, including model explainability, bias assessment, privacy safeguards, human oversight, and appropriate handling of sensitive data.
• Develop and maintain monitoring capabilities to detect model drift, performance degradation, operational failures, and other conditions requiring corrective action.
• Implement safeguards for generative AI applications, including prompt management, output validation, access restrictions, and human-in-the-loop review where required.
• Collaborate with VA stakeholders and technical teams to evaluate AI/ML use cases, assess technical feasibility, and establish production readiness criteria.
• Troubleshoot AI/ML platform and deployment issues, optimize model performance and resource utilization, and support reliable production operations.
• Develop technical documentation, implementation guidance, and reusable reference materials to support adoption and ongoing operation of AI/ML capabilities.
• Contribute technical findings, operational metrics, and recommendations to the Summit AI/ML Health Report and related Government reporting requirements.

Minimum Requirements:

• Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related technical discipline, or an equivalent combination of education and relevant professional experience.
• Seven or more years of professional experience in machine learning engineering, artificial intelligence development, data science engineering, or a related technical discipline.
• Demonstrated experience deploying, scaling, and supporting AI/ML solutions in enterprise production environments.
• Hands-on experience with Microsoft Azure AI/ML technologies, Azure Databricks, or comparable enterprise AI/ML platforms.
• Strong proficiency in Python and commonly used machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Experience developing machine learning pipelines for model training, evaluation, deployment, and monitoring.
• Experience implementing MLOps practices, including model registries, version control, automated testing, and Continuous Integration and Continuous Delivery (CI/CD) workflows.
• Knowledge of predictive modeling, natural language processing, and generative AI technologies and their practical enterprise applications.
• Experience integrating AI/ML solutions with enterprise data platforms, application programming interfaces (APIs), and cloud-based services.
• Understanding of responsible AI principles, including model explainability, bias mitigation, privacy protection, and human oversight.
• Strong analytical, troubleshooting, communication, and technical collaboration skills.
• Ability to meet VA personnel vetting, background investigation, and system access requirements.
• The ability to travel for 1-2 domestic business trips per year.

Preferred Qualifications:

• Direct experience supporting VA or other federal agency AI/ML modernization initiatives.
• Experience implementing enterprise AI/ML capabilities in Microsoft Azure Government cloud environments.
• Experience developing and deploying large language model (LLM) applications, including retrieval-augmented generation (RAG) and prompt orchestration.
• Experience implementing AI/ML monitoring for model drift, bias, data quality, and operational performance at enterprise scale.
• Experience working with sensitive healthcare data, including Protected Health Information (PHI), and federal privacy and security requirements.
• Experience developing reusable AI/ML accelerators, reference architectures, or self-service capabilities for multiple customer teams.
• Familiarity with federal responsible AI guidance, including the National Institute of Standards and Technology (NIST) AI Risk Management Framework.
• Microsoft Certified: Azure AI Engineer Associate or comparable AI/ML certification.

Benefits (including but not limited to):

• Health, dental, and vision plans
• Optional FSA
• Paid parental leave
• Safe Harbor 401(k) with employer contributions 100% vested from day 1
• Paid time off and 11 paid holidays
• No cost group term life/AD&D plan, and optional supplemental coverage
• Pet insurance
• Monthly phone and internet stipend
• Tuition and training reimbursement