AI/Machine Learning Engineer
Initiate Government Solutions, LLC.
Hybrid
Washington, DC, US
Full Time
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.
Assignment of Work and Travel:
This is a remote access assignment. The Candidate will work remotely daily and will remotely access VA systems and therein use approved VA provided communications systems. Travel is not required; however, the candidate may be required to attend onsite client meetings as requested.
The AI/Machine Learning Engineer will work alongside a team of highly skilled developers and engineers in the development of AI applications. A motivated and qualified candidate will not only have hands-on development experience in (JavaScript, Python or Java) but also a willingness to collaborate with teams to solve problems. Together we’re accelerating our client’s digital transformation through the building and deployment of data-driven, scalable AI solutions.
Responsibilities and Duties (Included but not limited to):
- 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
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
Successful IGS employees embody the following Core Values:
- Integrity, Honesty, and Ethics: We conduct our business with the highest level of ethics. Doing things like being accountable for mistakes, accepting helpful criticism, and following through on commitments to ourselves, each other, and our customers.
- Empathy, Emotional Intelligence: How we interact with others including peers, colleagues, stakeholders, and customers’ matters. We take collective responsibility to create an environment where colleagues and customers feel valued, included, and respected. We work within a diverse, integrated, and collaborative team to drive towards accomplishing the larger mission. We conscientiously and meticulously learn about our customers’ and end-users’ business drivers and challenges to ensure solutions meet not only technical needs but also support their mission.
- Strong Work Ethic (Reliability, Dedication, Productivity): We are driven by a strong, self-motivated, and results-driven work ethic. We are reliable, accountable, proactive, and tenacious and will do what it takes to get the job done.
- Life-Long Learner (Curious, Perspective, Goal Oriented): We challenge ourselves to continually learn and improve ourselves. We strive to be an expert in our field, continuously honing our craft, and finding solutions where others see problems.
Compensation: There are a host of factors that can influence final salary, including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications.
Benefits: Initiate Government Solutions offers competitive compensation and a robust benefits package, including comprehensive medical, dental, and vision care, matching 401K 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, an education assistance program with potential merit increases for obtaining a work-related certification, employee recognition, and referral programs, spot bonuses, and other benefits that help provide financial protection for the employee and their family.
Initiate Government Solutions participates in the Electronic Employment Verification Program.
AI/Machine Learning Engineer
Hybrid
Washington, DC, US
Full Time
August 12, 2025