Senior AI​/ML Engineer; Public Trust Security Clearance

Location:

Bethesda, MD (Hybrid) Clearance:
Public Trust (Role may require additional background investigations)

Employment Type:

Full-Time US Citizenship is Required

Praescient Analytics is seeking a highly experienced Senior AI/ML Engineer to support a mission‑critical federal analytics and artificial intelligence modernization program. This role is responsible for designing, engineering, deploying, and operating production‑grade AI and machine learning systems that support real‑time decision‑making, advanced analytics, and public safety outcomes. The Senior AI/ML Engineer owns the end‑to‑end machine learning lifecycle, from data ingestion and model development through deployment, monitoring, and governance.

This position plays a key role in operationalizing advanced analytics, building scalable MLOps pipelines, and integrating AI capabilities into cloud‑native systems within a highly regulated federal environment.

• Design, develop, train, and optimize machine learning and deep learning models supporting predictive analytics, classification, anomaly detection, NLP, and AI‑assisted decision support.
• Apply advanced ML techniques using supervised, unsupervised, and semi‑supervised learning approaches.
• Design and implement end‑to‑end MLOps pipelines supporting model training, validation, versioning, deployment, and rollback.
• Deploy models into production environments using Microsoft Azure ML, containerization, and CI/CD pipelines.
• Implement model monitoring, performance tracking, and drift detection to ensure long‑term reliability and accuracy.
• Build and maintain AI solutions leveraging Microsoft Azure services, including:
  • Azure Machine Learning
  • Azure Data Lake Storage
  • Azure Synapse Analytics
• Integrate AI/ML solutions with existing data platforms, APIs, and analytics services.
• Optimize AI workloads for cost, performance, and reliability in cloud environments.
• Ensure AI systems adhere to federal standards for responsible AI, transparency, explainability, and auditability.
• Support model documentation, validation artifacts, and compliance reporting.
• Collaborate with governance and stakeholder teams to ensure models are suitable for high‑impact decision‑making.
• Work closely with data scientists, data engineers, analysts, architects, and Agile project managers in a fast‑paced Agile delivery environment.
• Mentor junior engineers and contribute to shared engineering standards and best practices.

• Minimum of 5+ years of experience designing, deploying, and operating production AI/ML systems.
• Demonstrated experience moving models from research or prototype stages into production environments.
• Proven experience supporting AI systems in mission‑critical or regulated settings.
• Bachelor's Degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field – or equivalent professional experience.
• Experience supporting federal, public‑sector, or other regulated environments.
• Expert proficiency in Python and AI/ML frameworks such as PyTorch and/or Tensor Flow.
• Strong experience with machine learning libraries including Scikit‑learn, Num Py, and Pandas.
• Hands‑on experience with Microsoft Azure AI/ML services, particularly Azure Machine Learning.
• Experience building CI/CD pipelines for ML workflows.
• Familiarity with containerization (Docker) and model deployment patterns.
• Experience with SQL and data integration for ML workloads.
• Proficiency with Git‑based version control and collaborative development.
• Strong written and verbal communication skills.
• Ability to explain complex AI/ML concepts to technical and non‑technical stakeholders.
• Proven ability to lead technical efforts and collaborate across multidisciplinary teams.
• Minimum of a Public Trust (U.S. Citizenship is Required) clearance.

• Master's or Ph.D. in Computer Science, Machine Learning, Data Science, Engineering, or a related field – or equivalent professional experience.
• Familiarity with AI agents, vector databases, large language models (LLMs), or Copilot‑style architectures.
• Azure certifications (AI Engineer, Data Scientist, or related).
• Experience with streaming or near‑real‑time…