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Azure Ai Document Intelligence Jobs in Silver Spring, MD

Virtual Networx

AI/ML Engineer

Mclean, VA · On-site

Build scalable ML pipelines using MLflow, Kubeflow, Databricks, AWS, Azure, or Google Cloud ... Document models, architectures, workflows, and technical processes. Required Skills * Python

Ezenius Inc

AI Architect

Catonsville, MD · Remote

$150K - $200K/yr

AI Policy Expert with experience in AWS/Azure AI, Sagemaker, AI modeling, neural networks Position ... other documentation associated with AI. Education · Bachelor's Degree in Computer Science ...

Ezenius Inc

AI Architect

Catonsville, MD · Remote

$150K - $200K/yr

AI Policy Expert with experience in AWS/Azure AI, Sagemaker, AI modeling, neural networks Position ... other documentation associated with AI. Education · Bachelor's Degree in Computer Science ...

System One

AI QA Analyst - 100% REMOTE

Washington, DC · Remote

Validate Retrieval-Augmented Generation (RAG) solutions utilizing Azure AI Search, Azure AI Foundry ... Strong analytical, troubleshooting, and documentation skills * Excellent stakeholder engagement and ...

SES

Sr AI Platform Engineer - ZL

Centreville, VA · On-site

Integrate Azure AI Foundry and AWS Bedrock for approved model hosting and model routing. Develop ... Developer Enablement Create onboarding documentation, sample projects, reference architectures ...

System One

AI QA Analyst - 100% REMOTE

Washington, DC · Remote

Validate Retrieval-Augmented Generation (RAG) solutions utilizing Azure AI Search, Azure AI Foundry ... Strong analytical, troubleshooting, and documentation skills * Excellent stakeholder engagement and ...

System One

AI QA Analyst - 100% REMOTE

Washington, DC · Remote

Validate Retrieval-Augmented Generation (RAG) solutions utilizing Azure AI Search, Azure AI Foundry ... Strong analytical, troubleshooting, and documentation skills * Excellent stakeholder engagement and ...

A-TEK Inc.

Federal AI Solutions Engineer

Mclean, VA · On-site +1

... Data Intelligence, and Agile Engineering teams. * Contribute to technical documentation ... Microsoft Azure Fundamentals (AZ-900) or Azure AI Fundamentals (AI-900) Preferred Qualifications

A-TEK Inc.

Federal AI Solutions Engineer

Mclean, VA · On-site

... Data Intelligence, and Agile Engineering teams. * Contribute to technical documentation ... Microsoft Azure Fundamentals (AZ-900) or Azure AI Fundamentals (AI-900) Preferred Qualifications

KLDiscovery

AI Architect

Mclean, VA · On-site

$190K - $230K/yr

The work is hard in ways that matter: documents are messy and adversarial, the stakes are real ... Define and implement how we select, triage, and route across models (Azure OpenAI, Anthropic, open ...

Revolutional, LLC

Senior SharePoint Developer

Mclean, VA · On-site +1

$120 - $140K/hr

Artificial Intelligence & Microsoft AI Solutions * Design and implement AI-powered solutions ... AI Search (Azure AI Search) * Develop intelligent document processing and content management ...

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All JobsAzure Ai Document Intelligence JobsAzure Ai Document Intelligence Jobs in Silver Spring, MD

Azure Ai Document Intelligence information

What is Azure AI Document Intelligence?

Azure AI Document Intelligence is a cloud-based service provided by Microsoft Azure that uses artificial intelligence to extract, analyze, and process information from documents such as invoices, receipts, forms, and more. It helps automate data extraction by recognizing key fields and values, turning unstructured data into structured, usable information. This service is commonly used to streamline document-heavy workflows, reduce manual data entry, and improve operational efficiency for businesses.

What are some common challenges faced by professionals working with Azure AI Document Intelligence, and how can they be addressed?

Professionals working with Azure AI Document Intelligence often encounter challenges such as handling documents with complex layouts, ensuring high accuracy in data extraction, and integrating the service into existing workflows. Overcoming these challenges typically involves leveraging pre-trained models, customizing training with domain-specific data, and collaborating closely with developers and business analysts to fine-tune extraction processes. Regularly testing the models and staying updated with Azure’s latest features can also help improve outcomes and streamline document processing within teams.

What are the key skills and qualifications needed to thrive as an Azure AI Document Intelligence Specialist, and why are they important?

To excel as an Azure AI Document Intelligence Specialist, you need a solid understanding of cloud computing, machine learning, and document processing, typically supported by a degree in computer science or a related field. Familiarity with Microsoft Azure services, especially AI Document Intelligence (formerly Form Recognizer), as well as experience with APIs, Python, and data integration tools is crucial. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret business needs and deliver tailored AI solutions. These competencies ensure accurate extraction and processing of information from documents, driving automation and efficiency in enterprise workflows.

What is the difference between Azure Ai Document Intelligence vs Data Scientist?

AspectAzure Ai Document IntelligenceData Scientist
Primary FocusAutomating document processing and extracting insights from unstructured data using AIAnalyzing data to develop models, insights, and predictions for business decisions
Required SkillsAI/ML, OCR, NLP, cloud services, data preprocessingStatistics, programming (Python/R), machine learning, data analysis
Work EnvironmentCloud platforms, AI tools, enterprise document workflowsData analysis environments, research labs, business analytics
CertificationsAzure certifications, AI/ML certificationsData Science certifications, Python/R certifications

Azure Ai Document Intelligence focuses on automating document processing using AI technologies, while Data Scientists analyze data to build predictive models. Both roles require AI and data analysis skills but serve different purposes within the data ecosystem.

What are popular job titles related to Azure Ai Document Intelligence jobs in Silver Spring, MD?

For Azure Ai Document Intelligence jobs in Silver Spring, MD, the most frequently searched job titles are:

What job categories do people searching Azure Ai Document Intelligence jobs in Silver Spring, MD look for?

The top searched job categories for Azure Ai Document Intelligence jobs in Silver Spring, MD are:

What cities near Silver Spring, MD are hiring for Azure Ai Document Intelligence jobs?

Cities near Silver Spring, MD with the most Azure Ai Document Intelligence job openings:

Azure Ai Document Intelligence jobs near you

AI/ML Engineer

Virtual Networx

Mclean, VA • On-site

Other

Posted 22 days ago

Job description

Role: AI/ML Engineer
Experience: 10+ Years
Duration: 12 months
Location: MC Lean , VA

Skills: Python, Machine Learning, Deep Learning, Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy, SQL, NLP, Computer Vision, Generative AI, LLM, Prompt Engineering, RAG, Vector Databases, REST APIs

Responsibilities:

  • Design, develop, and deploy Machine Learning and AI solutions for business applications.
  • Build and optimize ML models for classification, regression, forecasting, recommendation, and NLP use cases.
  • Develop data preprocessing, feature engineering, model training, and evaluation pipelines.
  • Work with Python, Pandas, NumPy, Scikit-learn, TensorFlow, and/or PyTorch.
  • Develop and integrate Generative AI and LLM-based solutions where applicable.
  • Work with OpenAI/LLM APIs, prompt engineering, embeddings, vector databases, and RAG architectures.
  • Build scalable ML pipelines using MLflow, Kubeflow, Databricks, AWS, Azure, or Google Cloud Platform.
  • Deploy models through REST APIs, Docker, Kubernetes, and cloud platforms.
  • Monitor model performance, data quality, drift, and production issues.
  • Collaborate with Data Engineers, Software Engineers, Data Scientists, Product Owners, and business stakeholders.
  • Perform model tuning, experimentation, validation, and performance optimization.
  • Implement MLOps practices for CI/CD, model versioning, experiment tracking, and automated deployment.
  • Ensure AI solutions meet requirements for security, scalability, reliability, and responsible AI.
  • Document models, architectures, workflows, and technical processes.

Required Skills

  • Python
  • Machine Learning
  • Deep Learning
  • Scikit-learn
  • TensorFlow / PyTorch
  • Pandas / NumPy
  • SQL
  • NLP / Computer Vision as applicable
  • Generative AI / LLM
  • Prompt Engineering
  • RAG
  • Vector Databases
  • REST APIs
  • Docker / Kubernetes
  • Cloud: AWS / Azure / Google Cloud Platform
  • Git
  • MLOps / MLflow

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