AI/Machine Learning Engineer

Initiate Government Solutions•Washington, DC

9h•Remote

About The Position

Initiate Government Solutions (IGS), a Woman-Owned Small Business and remote IT services provider supporting federal partners, is pipelining candidates for a remote AI/Machine Learning Engineer role supporting federal healthcare work. Candidates may be contacted as opportunities become available. The engineer will work with developers and engineers to build and deploy data-driven, scalable AI solutions. The role includes developing machine learning applications for clinical decision-making, predictive analytics, health outcomes research, and healthcare operations. Work is performed remotely, with remote access to VA systems and approved VA-provided communications systems. Travel is not required, though attendance at onsite client meetings may be requested. The position also involves working with healthcare data and federal platforms, protecting sensitive information, documenting and monitoring model lifecycles, and collaborating with clinicians, program managers, data scientists, and software developers. The role supports IGS’s mission of delivering tailored, innovative solutions and exceptional service to federal healthcare partners.

Requirements

Bachelor’s degree or higher in Computer Science, Data Science, Artificial Intelligence/Machine Learning, Mathematics/Statistics, Biomedical Engineering, Health Informatics, Electrical Engineering, or Computer Engineering.
At least 4 years of experience in software and machine learning engineering.
Strong knowledge of natural language processing (NLP) and transformer models.
At least 5 years of proficiency in Python and hands-on experience with ML libraries such as TensorFlow, PyTorch, or Hugging Face Transformers.
Proven experience building scalable, cloud-based AI/ML solutions and enhancing custom question-answering mapping/workflows.
Expertise across 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, CI/CD pipelines tailored for ML workflows, model version control, and real-time performance monitoring.
Ability to obtain and maintain a Public Trust.
Passion for developing team-oriented solutions to complex engineering problems.
Excellent communication skills and attention to detail.
Analytical mindset and problem-solving aptitude.
Strong organizational skills.

Nice To Haves

Familiarity with federal AI governance frameworks and compliance standards, such as NIST AI RMF and FedRAMP.
Master’s degree in one of the listed fields.
Experience with Python, R, TensorFlow, PyTorch, Scikit-learn, AWS SageMaker, Azure ML, Databricks, Apache Spark, Power BI, Tableau, Plotly, Git, GitHub, or GitLab.
Active VA Public Trust.
Prior experience supporting a VA program.
Prior successful experience working remotely.

Responsibilities

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

Benefits

Comprehensive medical, dental, and vision care.
Matching 401(k) and profit sharing.
Paid time off.
Training time for personal development.
Flexible spending accounts.
Employer-paid life insurance.
Employer-paid short- and long-term disability coverage.
Education assistance program, with potential merit increases for obtaining a work-related certification.
Employee recognition and referral programs.
Spot bonuses.