Description:
Founded in 2007, Initiate Government Solutions (IGS) a Woman Owned Small Business. We are a fully remote IT services provider that delivers innovative Enterprise IT and Health Services solutions across the federal sector. Our focus is on data analytics, health informatics, cloud migration, and the modernization of federal information systems.
IGS uses ISO 9001:2015, 20000-1:2018, 27001:2013, 28001:2007, CMMI/SVC3, CMMI/DEV3 best practices, and PMBOK® methods to provide clients with a strategy to build solid foundations to grow capabilities and revenue. Our range of IT services and delivery methodologies are tailored to our customers’ unique needs to achieve maximum value.
IGS is currently pipelining for a remote AI/Machine Learning Engineer to support our work within the federal healthcare industry.

PREFERRED QUALIFICATIONS AND CORE COMPETENCIES:

• Master’s degree in one of the above-mentioned fields
• Preferred Tools & Environments: Python, R, TensorFlow, PyTorch, Scikit-learn, AWS (SageMaker), Azure ML, Databricks, Apache Spark, Power BI, Tableau, Plotly, Git, GitHub/GitLab
• Active VA Public Trust
• Prior experience supporting a VA program
• Prior, successful experience working in a remote environment

Requirements:

• Bachelor’s degree or higher in one of the following disciplines, Computer Science, Data Science, Artificial Intelligence / Machine Learning, Mathematics / Statistics, Biomedical Engineering, Health Informatics, Electrical or Computer Engineering
• 4+ years of experience in software and machine learning engineering.
• Strong knowledge of natural language processing (NLP) and transformer models.
• 5+ years proficiency in Python and hands-on experience with ML libraries like TensorFlow, PyTorch, or Hugging Face Transformers.
• Proven experience building scalable, cloud-based AI/ML solutions and enhancing custom question answering mapping/workflows.
• Expertise in the full ML pipeline, including data processing, model training, serving, and monitoring.
• Knowledge of NLP architectural strategies such as Retrieval-Augmented Generation, Knowledge Graphs, and Agentic Graphs.
• Expertise in MLOps best practices, including Infrastructure as Code (IaC), CI/CD pipelines tailored for ML workflows, model version control, and real-time performance monitoring to ensure scalable and reliable AI/ML systems.
• Familiarity with federal AI governance frameworks and compliance standards (e.g., NIST AI RMF, FedRAMP) is a plus.
• Passion for developing team-oriented solutions to complex engineering problems
• Excellent communication skills and attention to detail
• Analytical mind and problem-solving aptitude
• Ability to obtain and maintain a Public Trust
• Strong organizational skill

• Design, develop, and deploy machine learning and deep learning models to support clinical decision-making, predictive analytics, and health outcomes research.
• Fine-tune models for high performance using healthcare-specific data, including EHRs, claims, imaging, and structured/unstructured text.
• Collaborate with data engineers to clean, preprocess, and normalize healthcare data in compliance with federal data standards (e.g., HL7, FHIR).
• Build scalable ML pipelines that integrate with federal data platforms and cloud services (e.g., VA’s Lighthouse API, Azure Government, AWS GovCloud).
• Ensure AI/ML solutions meet federal regulations, including HIPAA, FISMA, FedRAMP, and VA Information Security requirements.
• Implement differential privacy, encryption, and access controls to safeguard sensitive health data.
• Contribute to the development of governance frameworks to ensure transparent, explainable, and bias-mitigated models.
• Document model lifecycle, from training to deployment, including risk assessments, validation reports, and audit trails.
• Work cross-functionally with program managers, clinicians, data scientists, and software developers to identify opportunities for AI/ML applications that improve healthcare delivery and veteran outcomes.
• Present complex machine learning findings in a way that is actionable and aligned with federal healthcare program goals.
• Stay updated on the latest developments in AI/ML applications for public health and healthcare operations.
• Prototype and test emerging AI technologies (e.g., NLP for clinical text, computer vision for imaging diagnostics) for possible integration into government systems.
• Monitor deployed models for drift, accuracy, and operational effectiveness over time.
• Maintain model retraining schedules based on new data inputs or policy changes.
• Prepare comprehensive documentation and reports for internal stakeholders and external oversight (e.g., OMB, GAO, IG audits).
• Develop dashboards and visualizations to track performance metrics, patient outcomes, and utilization trends impacted by AI/ML tools.

Requirements:

• Bachelor’s degree or higher in one of the following disciplines, Computer Science, Data Science, Artificial Intelligence / Machine Learning, Mathematics / Statistics, Biomedical Engineering, Health Informatics, Electrical or Computer Engineering
• 4+ years of experience in software and machine learning engineering.
• Strong knowledge of natural language processing (NLP) and transformer models.
• 5+ years proficiency in Python and hands-on experience with ML libraries like TensorFlow, PyTorch, or Hugging Face Transformers.
• Proven experience building scalable, cloud-based AI/ML solutions and enhancing custom question answering mapping/workflows.
• Expertise in the full ML pipeline, including data processing, model training, serving, and monitoring.
• Knowledge of NLP architectural strategies such as Retrieval-Augmented Generation, Knowledge Graphs, and Agentic Graphs.
• Expertise in MLOps best practices, including Infrastructure as Code (IaC), CI/CD pipelines tailored for ML workflows, model version control, and real-time performance monitoring to ensure scalable and reliable AI/ML systems.
• Familiarity with federal AI governance frameworks and compliance standards (e.g., NIST AI RMF, FedRAMP) is a plus.
• Passion for developing team-oriented solutions to complex engineering problems
• Excellent communication skills and attention to detail
• Analytical mind and problem-solving aptitude
• Ability to obtain and maintain a Public Trust
• Strong organizational skills