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Machine Vision Application Engineer Jobs in Washington, VA

Serioplast

Machine Operator

Mount Jackson, VA · On-site

$15.75 - $18.75/hr

Vision insurance Sounds like a fit? We'd love to hear from you! Want to know more about us? Check ... Upon sending their application, the candidate grants specific consent to the processing of personal ...

Rochester Cable

Be Seen First

Product Engineer

Culpeper, VA · On-site

$96K - $115K/yr

Support the Business Office in their efforts to assist customers in resolving application problems ... machine capabilities, design specifications, and communicate engineering changes and material needs ...

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All JobsMachine Vision Application Engineer JobsMachine Vision Application Engineer Jobs in Washington, VA

Machine Vision Application Engineer information

See Washington, VA salary details

$53.2K

$116.7K

$160.3K

How much do machine vision application engineer jobs pay per year?

As of Aug 17, 2026, the average yearly pay for machine vision application engineer in Washington, VA is $116,709.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,600.00 and $142,300.00 per year, depending on experience, location, and employer.

What is a machine vision application engineer?

A Machine Vision Application Engineer is a technical professional who designs, develops, and implements machine vision systems used for automated inspection, measurement, and guidance in manufacturing and industrial environments. They work with cameras, sensors, lighting, and image processing software to create solutions that help machines 'see' and interpret visual information. Their role often involves collaborating with clients to understand application requirements, selecting appropriate hardware and software, and ensuring successful system integration. Machine Vision Application Engineers play a key role in improving product quality, production efficiency, and automation processes.

How does a machine vision application engineer typically collaborate with other departments during a project?

Machine Vision Application Engineers frequently work in cross-functional teams, collaborating closely with software developers, mechanical engineers, and production staff to ensure vision systems integrate seamlessly into manufacturing processes. They are often involved from the initial requirements gathering stage through to implementation and troubleshooting, providing technical expertise and translating complex imaging needs into practical solutions. Regular communication with quality assurance and operations teams is also common, as these engineers help fine-tune systems to maintain accuracy and efficiency on the production floor.

What are the key skills and qualifications needed to thrive as a machine vision application engineer, and why are they important?

To thrive as a Machine Vision Application Engineer, you need a solid background in engineering or computer science, experience with image processing, and a strong understanding of optics and camera technologies. Familiarity with machine vision software (such as Cognex, Halcon, or OpenCV), programming languages (like C++ or Python), and industrial automation systems is typically required. Strong problem-solving skills, effective communication, and project management abilities help you excel in client-facing and cross-disciplinary environments. These skills are crucial for designing, implementing, and supporting robust vision systems that meet manufacturing and automation needs.

What is the difference between Machine Vision Application Engineer vs Computer Vision Engineer?

AspectMachine Vision Application EngineerComputer Vision Engineer
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with vision systemsBachelor's or higher in Computer Science, Electrical Engineering, or related; strong programming skills
Work EnvironmentManufacturing, automation, quality control settingsResearch labs, tech companies, AI development environments
Industry UsageIndustrial automation, robotics, manufacturingAI, autonomous vehicles, image analysis
Common Search/ComparisonYesYes

While both roles involve image processing and vision systems, the Machine Vision Application Engineer focuses on implementing vision solutions in industrial settings, whereas the Computer Vision Engineer works on developing algorithms and AI models for broader applications like autonomous vehicles and AI research.

What cities near Washington, VA are hiring for Machine Vision Application Engineer jobs?

Cities near Washington, VA with the most Machine Vision Application Engineer job openings:

Machine Vision Application Engineer jobs near you
Infographic showing various Machine Vision Application Engineer job openings in Washington, VA as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 16% Part Time, and 6% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $116,709 per year, or $56.1 per hour.

Image & Computer Vision AI Engineer

hatch IT

Washington, VA • On-site

Other

Re-posted 24 days ago

Job description

hatch I.T. is partnering with Babel Street to find an Image & Computer Vision AI Engineer. Please see details below:
About the Role
As an Engineer on the Image & Computer Vision AI team, you will play a hands-on role in developing and deploying computer vision capabilities that support Babel Street's intelligence applications. You will build systems that extract, analyze, and reason over visual data-enabling facial matching, object and scene understanding, geolocation and location inference from imagery, and multimodal intelligence workflows.
This role is execution-focused and suited for engineers with strong foundations in computer vision, image processing, and machine learning who want to apply their skills to real-world, mission-driven problems. You will work closely with AI, Product, and Engineering teams to deliver reliable, scalable, and cost-efficient vision capabilities, including integration with multimodal LLM systems that allow users to search and reason over images using natural language.
This is a hybrid role to be based out of either their Reston, VA/Washington DC office or their Somerville MA office.
About the Company
Babel Street is the trusted technology partner for the world's most advanced identity intelligence and risk operations. They deliver advanced AI and data analytics solutions providing unmatched, analysis-ready data regardless of language, proactive risk identification, 360-degree insights, high-speed automation, and seamless integration into existing systems. Babel Street empowers government and commercial organizations to transform high-stakes identity and risk operations into a strategic advantage. The actionable insights we deliver safeguard lives and protect critical assets around the world. Babel Street is headquartered in Reston, Virginia, with regional offices in Boston, MA and Cleveland, OH, and international offices in Australia, Canada, Israel, Japan, and the U.K.
Role Focus:
This role spans three practical execution areas:
Computer Vision & Image Analytics
You will implement and operate image analytics pipelines that support facial matching, object detection, scene understanding, and image similarity. This includes image preprocessing, feature extraction, model inference, evaluation, and performance optimization to meet mission-grade accuracy and latency requirements.
Geospatial & Location Inference from Imagery
You will contribute to capabilities that infer location, context, or environmental attributes from imagery-leveraging visual cues, metadata, and learned representations. This includes supporting image-based geolocation, landmark recognition, and contextual scene analysis used in intelligence workflows.
Multi-Modal AI & Image Search
You will support multimodal AI systems that combine vision models with LLMs, embeddings, and retrieval pipelines to enable natural-language search and reasoning over images and image collections. You will help integrate visual understanding into broader intelligence applications and workflows.
What you will do:
  • Build and maintain computer vision pipelines for image ingestion, preprocessing, inference, and evaluation.
  • Implement facial matching, and identity-related vision workflows in accordance with accuracy, safety, and compliance requirements.
  • Develop and support object detection, image similarity, and scene understanding models.
  • Contribute to image-based geolocation and location inference capabilities using visual features and contextual signals.
  • Support multimodal AI workflows that combine image embeddings with LLM-based search and reasoning.
  • Write clean, maintainable Python code and contribute to production services and APIs.
  • Assist with model evaluation, bias testing, and accuracy monitoring for vision systems.
  • Optimize inference pipelines for performance, scalability, and cost efficiency (GPU usage, batching, model selection).
  • Collaborate with Product and Engineering teams to integrate vision capabilities into user-facing intelligence applications.

What you will bring:
Required
  • 3+ years of experience in computer vision, image processing, or applied machine learning.
  • Hands-on experience with computer vision models and techniques (e.g., CNNs, transformers for vision, feature embeddings).
  • Experience building or integrating image analytics such as facial recognition, object detection, or image similarity.
  • Strong programming skills in Python; experience with common CV/ML libraries (PyTorch, TensorFlow, OpenCV, etc.).
  • Solid understanding of machine learning fundamentals, model evaluation, and performance tradeoffs.
  • Experience working with large image datasets and production ML pipelines.
  • Ability to work collaboratively in a fast-moving, mission-driven engineering environment.

Preferred
  • Experience with facial matching or biometric systems in regulated or high-stakes environments.
  • Experience with image-based geolocation or scene/location inference.
  • Familiarity with multimodal AI systems, including combining vision models with LLMs or natural-language search.

Education:
  • Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field required.
    Advanced degree is a plus but not required.

$140,000 - $170,000 a year
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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