OverviewDecisionPoint seeks an AI/ML Engineer to rapidly develop prototypes, implement integrations, and operationalize AI/ML capabilities that support a large federal and DoD-aligned mission environment. This role builds fast proofs-of-concept, API-based integrations, and lightweight user-facing components that validate new AI/ML ideas and help transition successful models into production dashboards and applications.
The AI/ML Engineer collaborates closely with data scientists, dashboard teams, developers, and PMO leadership to ensure AI/ML models are usable, optimized, and appropriately embedded into mission workflows.
This position is fully remote.
Duties & Responsibilities
The AI/ML Engineer will:
- Develop rapid prototypes, microservices, APIs, widgets, and integrations to validate new AI/ML concepts.
- Integrate ML models into dashboards, applications, and operational workflows.
- Build lightweight UI components that demonstrate how AI outputs can be consumed.
- Optimize ML pipelines for performance, scalability, and efficient inference.
- Collaborate with AI/ML Architects and Data Scientists to operationalize models and automation logic.
- Support data ingestion, feature engineering, and preprocessing tasks for prototype development.
- Build API wrappers, routing logic, and connector services for ML model interactions.
- Validate prototype functionality, performance, error handling, and model integration.
- Contribute to documentation of models, prototypes, integrations, and deployment patterns.
- Work with cybersecurity teams to ensure integration patterns align with security requirements.
- Recommend improvements based on usability testing, technical feedback, and mission needs.
Qualifications
Clearance Requirement
Candidate must possess a Tier 2 Moderate Risk Public Trust (from any federal agency) or an active Secret clearance or higher.
Education (Required)
Bachelors degree in Data Science, Computer Science, Artificial Intelligence/Machine Learning, Statistics, or a related field.
Experience (Required)
- Minimum 5 years of experience in software development, AI/ML engineering, or data-driven application development.
- Experience building API-driven prototypes, integrations, or microservices.
- Experience integrating ML models into dashboards, applications, or mission workflows.
- Experience working with data scientists or ML engineers to transition models to production.
Technical Knowledge (Required)
- Proficiency with Python, JavaScript, or similar development languages.
- Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-Learn).
- Experience building REST APIs, web services, or integration layers.
- Understanding of data pipelines, preprocessing steps, and ML lifecycle workflows.
Technical Knowledge (Preferred)
- Experience with AWS cloud services or ML platforms.
- Familiarity with front-end frameworks for rapid prototyping.
- Experience with CI/CD pipelines and DevSecOps tooling.
Certifications
Required:
Preferred:
- AI/ML engineering or cloud certifications
- Scrum Master or Agile certifications
Skills
- Strong development and prototyping skills.
- Ability to translate AI/ML concepts into functional components quickly.
- Strong collaboration skills with cross-functional technical teams.
- Excellent communication and documentation skills.
- High attention to detail in integration, testing, and optimization work.
