Artificial Intelligence and Machine Learning Engineer

Salary Range: 100000 to 115000 (Currency: USD) (Pay period: per-year-salary)

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