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Analytica

Public-sector data-driven consulting and technology services

AI-ML Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBethesda, MD, USAIn-person

About the Job

Requirements

  • U.S. citizenship is required, and the candidate must be able to secure public trust clearance.
  • At least 3 years of hands-on experience developing and deploying AI/ML solutions in production environments is required.
  • Proficiency in Python, including data analysis and machine learning libraries such as Pandas, NumPy, scikit-learn, PyTorch, and TensorFlow, is required.
  • Knowledge of machine learning concepts, model selection, training, validation, and evaluation techniques is required.
  • Experience with Microsoft Azure services for data and AI workloads, including Azure Machine Learning, Azure Data Lake Storage Gen2, Azure Synapse Analytics (SQL and/or Spark), and Azure Data Factory, is required.
  • Working knowledge of MLOps concepts, including CI/CD pipelines, version control, and model lifecycle management, is required.
  • Experience collaborating in Agile development environments and using modern DevOps tools such as Azure DevOps and GitHub is required.
  • A bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field, or equivalent practical experience, is required.

Responsibilities

  • Build, maintain, and optimize Azure-based data pipelines and workflows using Azure Data Factory, ADLS Gen2, Synapse Analytics, Azure SQL, Python, and SQL.
  • Support batch and near-real-time data ingestion, transformation, enrichment, and aggregation to deliver analytics- and reporting-ready datasets.
  • Implement data quality checks, schema management, and validation to ensure reliable, trusted, and well-documented data.
  • Build secure data pipelines, integrate structured and unstructured data, and support NLP/ML workloads.
  • Configure, monitor, and enhance enterprise AI capabilities across Azure and other approved platforms.
  • Ensure compliance with federal architecture standards, enterprise architecture guidelines, and security controls.
  • Produce architecture artifacts, test plans, security documentation, and operational runbooks according to sprint requirements.
  • Contribute to CI/CD pipelines, monitoring, troubleshooting, and performance tuning to ensure reliable data operations.
  • Work within Agile teams and collaborate with senior engineers, analysts, and stakeholders to deliver well-defined data requirements.

Desired Qualifications

  • Microsoft Certified: Azure AI Engineer Associate certification.
  • Experience with Copilot Studio or AI agent development, including orchestration and integration with APIs and data sources.
  • Familiarity with feature stores, vector databases, or retrieval-augmented generation patterns.
  • Exposure to event-driven or streaming architectures such as Azure Event Hubs.
  • Knowledge of responsible AI practices, including fairness, explainability, model governance, and security considerations.
  • Experience working in regulated or mission-driven environments.
  • Azure certifications related to AI, data engineering, or cloud architecture.

About the Company

Analytica

Public-sector data-driven consulting and technology services

Analytica provides data-driven consulting and technology services to U.S. public-sector agencies in health, civilian, and national security. Its offerings combine data analytics, systems integration, and technology implementation to help government entities modernize operations and improve decision-making. The company differentiates itself through a strong track record with public-sector modernization recognized by organizations like NYU’s Governance Lab, its SBA 8(a) and HUBZone certifications, and being named among Inc.’s fastest-growing U.S. companies for three consecutive years. Analytica’s goal is to enable government clients to use data and technology to deliver better services, increase efficiency, and strengthen national security.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Washington DC, District of Columbia
Founded
2007

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