Senior AI/ML Engineer; Public Trust
Listed on 2026-02-16
-
IT/Tech
AI Engineer, Machine Learning/ ML Engineer
Overview
Location: Bethesda, MD (Hybrid) |
Clearance: Public Trust (Role may require additional background investigations) |
Employment Type: Full-Time
US Citizenship is Required
Position OverviewPraescient 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.
Clearance: Minimum of a Public Trust (U.S. Citizenship is Required)
Preferred Qualifications- 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…
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