Summary
Written in English from the original postingTrilogy Federal is seeking an AI/ML Engineer to support VA Summit ATLAS by designing, deploying, and maintaining enterprise AI/ML platform capabilities, pipelines, and MLOps workflows. The role focuses on Azure AI/ML tooling, production deployment, monitoring, responsible AI controls, and reusable frameworks. The position is remote/Arlington, VA, contingent on award, and requires occasional domestic travel.
Job description
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
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