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Ai Image Recognition Jobs (NOW HIRING)

Babel Street

Image & Computer Vision AI Engineer

Reston, VA · On-site

$119K - $143K/yr

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 ...

eBay, Inc.

Director of Product, AI Listing

San Jose, CA · On-site

$224K - $300K/yr

This includes core ownership of Magical Listing-eBay's flagship solution that uses generative AI, image recognition, and automation to help sellers create compelling listings from a photo or text ...

Circana

VP II, AI Innovation - OCR (Level 21)

Role Overview The VP of AI Innovation - OCR/Image Recognition, will lead innovation, development, and execution of next generation AI-driven OCR and Image Recognition capabilities. This role will ...

GeoYeti

Expert Data Scientist

Augusta, GA

... image recognition - to geospatial problems * Develop and employ algorithms supporting GEOINT ... AWS AI/ML Specialty certification * Knowledge of the NSG TCPED (Tasking, Collection, Processing ...

GeoYeti

Expert Data Scientist

Augusta, GA · On-site

... image recognition - to geospatial problems * Develop and employ algorithms supporting GEOINT ... AWS AI/ML Specialty certification * Knowledge of the NSG TCPED (Tasking, Collection, Processing ...

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All JobsAi Image Recognition Jobs

Ai Image Recognition information

See salary details

$20.5K

$95.1K

$185.5K

How much do ai image recognition jobs pay per year?

As of Jun 16, 2026, the average yearly pay for ai image recognition in the United States is $95,090.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,000.00 and $132,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals working in AI image recognition roles?

Professionals in AI image recognition roles often encounter challenges such as managing large, complex datasets and ensuring high-quality data annotation for training models. Balancing model accuracy with computational efficiency is another frequent hurdle, especially when deploying solutions to production environments. Additionally, staying updated with rapidly evolving technologies and collaborating effectively with cross-functional teams such as data scientists, software engineers, and product managers is crucial for successful project outcomes.

What is the difference between Ai Image Recognition vs Computer Vision Engineer?

AspectAi Image RecognitionComputer Vision Engineer
Required CredentialsBachelor's or higher in CS, AI, or related fields; experience with ML frameworksBachelor's or higher in CS, Electrical Engineering, or related fields; expertise in image processing and algorithms
Work EnvironmentResearch labs, tech companies, AI startupsTech companies, robotics firms, autonomous vehicle companies
Industry UsageDeveloping models to identify and classify imagesDesigning systems for interpreting visual data in real-world applications

While Ai Image Recognition focuses on creating models to identify and classify images, Computer Vision Engineers develop broader systems that interpret visual data for practical applications. Both roles require similar educational backgrounds and often collaborate, but their core focuses differ: one on specific recognition tasks, the other on system development.

What are the key skills and qualifications needed to thrive as an AI Image Recognition Specialist, and why are they important?

To excel as an AI Image Recognition Specialist, you need strong skills in computer vision, machine learning, programming (especially Python), and a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), experience with image processing libraries (like OpenCV), and certifications in AI or data science are often required. Critical thinking, problem-solving, and effective collaboration are valuable soft skills that set candidates apart in this field. These capabilities ensure accurate model development, innovation, and reliable deployment of image recognition solutions in real-world applications.

What is AI image recognition?

AI image recognition is a technology that enables computers to identify and classify objects, people, places, and actions within digital images. It uses machine learning algorithms, particularly deep learning, to analyze visual data and recognize patterns. This technology is widely used in applications like facial recognition, medical imaging, autonomous vehicles, and content moderation. AI image recognition continues to improve as more data and advanced algorithms become available, making it increasingly accurate and versatile.
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Ai Image Recognition jobs near you

Image & Computer Vision AI Engineer

Hatch IT

Washington, VA • On-site

Full-time

Posted 23 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. 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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