AI/ML Architect

Overview 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. 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: - ITIL v4 Foundation 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 exp