AI/ML Architect

DecisionPoint | Cortek•,

2d•Remote

About The Position

DecisionPoint 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.

Requirements

Candidate must possess a Tier 2 Moderate Risk Public Trust (from any federal agency) or an active Secret clearance or higher.
Bachelor’s degree in Data Science, Computer Science, Artificial Intelligence/Machine Learning, Statistics, or a related field.
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.
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.
ITIL v4 Foundation certification.
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.

Nice To Haves

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.
AI/ML professional certifications.
Cloud practitioner or cloud security certifications.

Responsibilities

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.