OverviewDecisionPoint seeks an AI/ML Architect to design artificial intelligence pilots, machine learning pipelines, and advanced analytics models supporting a large federal and DoD-aligned mission environment. This role develops predictive analytics solutions, anomaly detection models for IT and cybersecurity operations, automated content classification capabilities, personalization algorithms, and behavioral analytics models.
The AI/ML Architect collaborates closely with data scientists, dashboard teams, engineering staff, cybersecurity analysts, and PMO leadership to translate mission needs into AI-driven prototypes and production-ready solutions. The role also supports experimentation, evaluation, and integration of AI/ML capabilities aligned with enterprise governance and modernization objectives.
This position is fully remote.
Duties & Responsibilities
The AI/ML Architect will:
- Design AI/ML pilots supporting predictive analytics, anomaly detection, behavioral analytics, and content automation.
- Build prototypes for IT and cybersecurity anomaly detection using operational, log, and behavioral datasets.
- Develop algorithms for personalization, content classification, and relevance scoring.
- Create end-to-end machine learning pipelines including preprocessing, feature engineering, model training, validation, and deployment.
- Work with system owners and cybersecurity teams to identify model inputs, risk indicators, and performance thresholds.
- Collaborate with dashboard developers to operationalize ML insights into mission dashboards.
- Evaluate new AI technologies, frameworks, and tools for mission applicability.
- Support data exploration, hypothesis testing, and experiment design.
- Produce documentation including model descriptions, assumptions, validation reports, and integration specifications.
- Ensure AI/ML models follow governance guidelines for accuracy, explainability, bias mitigation, and security compliance.
- Recommend optimization opportunities based on data-driven insights and trend analysis.
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)
Bachelor’s degree in Data Science, Computer Science, Artificial Intelligence/Machine Learning, Statistics, or a related field.
Experience (Required)
- Minimum 7 years of experience designing and implementing AI/ML models.
- Experience with anomaly detection, predictive analytics, behavioral analytics, or pattern recognition.
- Experience supporting AI/ML pilots or prototypes within federal, DoD, or mission-critical environments.
- Experience building machine learning pipelines and experiment designs.
Technical Knowledge (Required)
- Proficiency with ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
- Strong understanding of statistical modeling, anomaly detection, and predictive forecasting.
- Experience with Python, R, or similar programming languages.
- Familiarity with data pipelines, feature engineering, and data transformation.
Technical Knowledge (Preferred)
- Experience in cloud-based ML platforms (AWS Sagemaker, Azure ML, etc.).
- Knowledge of cybersecurity datasets and detection logic.
- Familiarity with LLMs, vector embeddings, or retrieval-augmented AI architectures.
Certifications
Required:
Preferred:
- AI/ML professional certifications
- Cloud practitioner or cloud security certifications
Skills
- Strong problem-solving and analytical abilities.
- Ability to communicate complex AI/ML concepts to technical and non-technical audiences.
- High attention to detail for model validation, accuracy, and performance tuning.
- Ability to work across multiple teams and integrate AI/ML results into broader program strategies.
- Strong documentation and communication skills for model explainability.
