Overview

DecisionPoint 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:

• ITIL v4 Foundation

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.