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Intelligent Document Processing Jobs (NOW HIRING)

Conversational AI oder Intelligent Document Processing Erfolgreich abgeschlossenes Studium der (Wirtschafts-)Informatik, (Wirtschafts-)Ingenieurwesen, Wirtschaftswissenschaften mit Informatikbezug ...

Intelligent Document Processing vs. Agentic workflows) to ensure optimal solution design. * Partner with IT Security, Cloud Platform teams, and system administrators to maintain, scale, and secure ...

AWS and Gen AI Engineer

Houston, TX · Remote

$109K - $131K/yr

AWS GenAI Engineer - Intelligent Document Processing and Data Pipelines Job Summary We are seeking an experienced AWS Generative AI Engineer to design and develop intelligent document-processing ...

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Intelligent Document Processing information

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How much do intelligent document processing jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for intelligent document processing in the United States is $20.63, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $24.52 per hour, depending on experience, location, and employer.

What is intelligent document processing?

Intelligent Document Processing (IDP) is a technology that uses artificial intelligence, machine learning, and optical character recognition (OCR) to automatically extract, classify, and process data from a wide variety of documents. This includes both structured forms and unstructured documents like emails, invoices, and contracts. IDP streamlines workflows by minimizing manual data entry, increasing accuracy, and accelerating the handling of large volumes of documents in industries such as finance, healthcare, and insurance.

What are the main challenges faced by professionals working in intelligent document processing, and how can they be addressed?

Professionals in Intelligent Document Processing (IDP) often encounter challenges such as handling diverse document formats, ensuring data accuracy, and integrating IDP solutions with existing systems. Managing unstructured data and constantly evolving document types requires strong analytical and technical skills. To overcome these challenges, it's important to stay current with the latest IDP software, collaborate closely with IT and business teams to define requirements, and continuously monitor and improve data extraction processes for accuracy and compliance.

What are the key skills and qualifications needed to thrive as an intelligent document processing specialist, and why are they important?

To thrive as an Intelligent Document Processing Specialist, you need a solid background in data analysis, document management, and familiarity with automation or AI-driven extraction tools, often supported by a degree in computer science or a related field. Expertise in technologies such as OCR (Optical Character Recognition), RPA (Robotic Process Automation), and platforms like UiPath or ABBYY is typically required, with certifications in these tools being advantageous. Strong problem-solving abilities, attention to detail, and effective communication are crucial soft skills for success in this role. These competencies ensure accurate data extraction, streamlined workflows, and successful collaboration across departments, ultimately driving operational efficiency.

What is the difference between Intelligent Document Processing vs Data Analyst?

AspectIntelligent Document ProcessingData Analyst
Required CredentialsTypically certifications in AI, OCR, or document managementDegree in statistics, mathematics, or related field
Work EnvironmentAutomation-focused, often in tech or finance sectorsData analysis, reporting, and visualization in various industries
Employer & Industry UsageUsed by companies automating document workflowsUsed by organizations analyzing data for insights

Intelligent Document Processing focuses on automating the extraction and management of data from documents using AI and OCR technologies. Data Analysts interpret and analyze data sets to provide business insights. While both roles involve data, Intelligent Document Processing emphasizes automation of document workflows, whereas Data Analysts focus on data interpretation and reporting.

What other helpful pages are available for Intelligent Document Processing?

Other pages related to Intelligent Document Processing:

Infographic showing various Intelligent Document Processing job openings in the United States as of September 2026, with employment types broken down into 2% As Needed, 81% Full Time, 12% Part Time, and 5% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $42,911 per year, or $20.6 per hour.

Senior Machine Learning Engineer - Intelligent Document Processing / Production AI Systems

Reston, VA

Pantheon Data LLC
Computing Infrastructure Providers, Data Processing, Web Hosting • 501 - 1,000 employees

$108K - $149K/yr

Full-time

Posted 14 days ago


Job description

Company Overview

Pantheon Data (a Kenific Holding company) is a private, small business based in the Washington, DC, area. Pantheon Data was founded in 2011, initially providing acquisition and supply chain management services to the US Coast Guard. Our service offerings have grown in the past ten years, including infrastructure resiliency, contact center operations, information technology, software engineering, program management, strategic communications, engineering, and cybersecurity. We have also grown our customer base to include commercial clients. The company has used this experience to expand our service offerings to other agencies within the Department of Homeland Security (DHS), the Department of Defense (DoD), and other Federal Civilian Agencies.

Position Overview

We are seeking a Senior Machine Learning Engineer to help build production-oriented AI and Intelligent Document Processing (IDP) systems. This role is for a hands-on engineer who can move beyond experiments and build working software that ingests, processes, analyzes, retrieves, and explains information from complex unstructured and semi-structured sources.

The ideal candidate has real depth in machine learning, NLP, OCR, computer vision, LLMs, and retrieval-based systems, but also has the broader engineering judgment to understand the system around the model: data pipelines, APIs, databases, cloud infrastructure, containers, testing, evaluation, observability, and production failure modes.

This is not a notebook-only, prompt-only, or research-only role. A successful candidate should be prepared to discuss specific systems they have built, including the data flow, model or inference architecture, deployment approach, evaluation strategy, failure modes, and what they personally implemented.

What This Role Will Work On

  • Design and build AI/ML capabilities for Intelligent Document Processing, including OCR post-processing, document parsing, NLP/LLM extraction, semantic search, retrieval, evidence grounding, and structured data generation.
  • Develop production-quality Python services, pipelines, and tooling that turn messy source documents into reliable, traceable, usable information.
  • Work across the full lifecycle of AI systems: data ingestion, preprocessing, model or LLM integration, evaluation, deployment, monitoring, and iterative improvement.
  • Build and improve systems that process PDFs, scanned documents, tables, forms, drawings, images, technical manuals, and other complex document types.
  • Collaborate with software engineers, data engineers, cloud engineers, product leads, customers, and leadership to turn ambiguous technical problems into working solutions.
  • Make practical engineering decisions about when to use deterministic logic, classical NLP, OCR, embeddings, LLMs, fine-tuned models, or human review workflows.
  • Helpestablishengineering standards for evaluation, reproducibility, model behavior, data quality, traceability, and responsible use of AI in customer-facingsystems.

Responsibilities

  • Design, implement, andmaintainML/AI software components for IDP and Generative AI systems.
  • Build data pipelines for unstructured and semi-structured data, including document ingestion, extraction, cleaning, enrichment, validation, and storage.
  • Develop and evaluate NLP, OCR, computer vision, embedding, retrieval, and LLM-based approaches for document understanding use cases.
  • Create APIs, internal tools, review interfaces, dashboards, orvalidationworkflows that allow engineers and users to inspect, correct, and trust system output.
  • Contribute production-quality code with clear structure, tests, logging, error handling, and documentation.
  • Deploy and support ML/AI services in cloud or containerized environments, including model serving, batch processing, and workflow automation.
  • Design evaluation approaches for extraction quality, retrieval quality, model behavior, hallucination risk, and end-to-end system performance.
  • Troubleshoot system behavior across model output, data quality, retrieval, schema design, infrastructure, latency, cost, and user workflow issues.
  • Mentor other engineers and help raise the technical quality of the team.
  • Communicate clearly with both technical and non-technical stakeholders, including project managers, customers, and executive leadership.

Required Skills and Experience

  • Bachelor's degree in Computer Science,Engineering, or a related technical fieldfrom an ABET accredited university.
  • 5+ years of professional hands-on experience in machine learning engineering, AI engineering, data science engineering, or a closely related software engineering role.Plusanadditional5 years of experience in technology and software engineering.
  • Demonstrated experience building AI/ML systems beyond notebooks, prototypes, or demos. Candidates should have shipped or supported pipelines, services, APIs, inference endpoints, evaluation harnesses, or production-facing tools.
  • Strong Python engineering experience, including readable, maintainable code; debugging; testing; packaging; and integration with other systems.
  • Hands-on experience with NLP, OCR, computer vision, LLMs, embeddings, semantic search, RAG, or other document-understanding techniques.
  • Experience working with unstructured or semi-structured data such as PDFs, scanned documents, forms, tables, images, logs, contracts, technical manuals, or engineering documentation.
  • Ability to design and reasonaboutend-to-end data flow: source data, preprocessing, transformation, model/inference step, persistence, API/service boundary, evaluation, and user-facing output.
  • Familiarity with common ML frameworks and tooling such asPyTorch, TensorFlow, scikit-learn, Hugging Face,MLflow, or similar technologies.
  • Experience with databases and data stores, including SQL and at least one relational or non-relational data platform.
  • Experience using Git-based development workflows, code review, issue tracking, and team-based software delivery practices.
  • Clear written and verbal communication skills, including the ability to explain technical tradeoffs, limitations, and failure modes.
  • Ability to work effectively remotely in cross-functional teams.
  • Ability to meet deadlines and produce quality work.
  • Proficient in Microsoft Suite software including Outlook, Word, Excel, SharePoint, and PowerPoint.

Preferred Skills and Experience

  • Direct experience with Intelligent Document Processing, document AI, OCR pipelines, table extraction, form extraction, layout-aware processing, or evidence-grounded retrieval.
  • Experience building, deploying, or operating LLM-backed systems, including inference serving, prompt/version management, model evaluation, retrieval, observability, or cost/latency management.
  • Experience with cloud platforms such as AWS or Azure, including storage,compute, serverless, networking basics, IAM, monitoring, or managed ML/AI services.
  • Experience with containers and deployment workflows, including Docker, Kubernetes, CI/CD pipelines, automated tests, and environment promotion.
  • Experience building user-facing or internal tools such as validation interfaces, review workflows, dashboards, admin tools, or lightweight full-stack applications.
  • Experience with data engineering tools such as pandas, NumPy, Spark/PySpark, Databricks, Airflow, or similar workflow/data platforms.
  • Experience with observability, performance profiling, or debugging tools such as Grafana, CloudWatch,TensorBoard, tracing tools, GPU profiling tools, or application logs.
  • Experience with evaluation design, benchmarking, reproducibility, statistical analysis, error analysis, or human-in-the-loop validation.
  • Bachelor's or advanced degree in Computer Science, Engineering, Mathematics, Physics, Statistics, Data Science, oranothertechnical discipline. Equivalent professional experience will also be considered.
  • Demonstrated ability to mentor junior developers or contribute to team technical direction.

Clearance Requirements

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements. Secret Clearance is required for continued employment.

Work Location: Reston, VA - Remote

  • Our company prioritizes the benefits of flexibility and collaboration, whether that happens in person or remotely.
  • If the position is remote or hybrid, you may periodically work from a Pantheon Data office location or client site.
  • If this position is assigned to a Pantheon Data office location or client site, you'll work with colleagues and clients in person, as needed for specific client requirements.

Interview Requirement: Candidates who are local to the area should be prepared to participate in an in-person interview as part of the selection process. Candidates outside the local area may be considered for a virtual interview.

Compensation

The salary range for this position is $140,000 - $200,000. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Benefits Overview

We are always looking for good people! Pantheon Data is committed to providing its employees with competitive salaries and benefits in order to increase employee satisfaction and productivity.In addition to our benefits, we also offer SmartBenefits through the Washington Metro Area Transportation Authority, where you specify an amount of your pre-tax wages be paid directly to your SmarTrip account. In some cases, tuition assistance may be available for continuing education expenses and certifications related to their position. Additional details may be found at https://pantheon-data.com/careers/

Pantheon Data Important Information

All qualified applicants will be considered for employment without regard to disability, status as a protected veteran, or any other status protected by applicable federal, state, local, or international law.

As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to our Talent Team at Recruiting@pantheon-data.com or by phone (571) 363-4020.

This company uses E-Verify to confirm each employee's work authorization. For more information, click here E-Verify Participation Poster