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Ai Image Recognition Jobs (NOW HIRING)

Citian

AI Integration Engineer

Washington, DC

$117K - $158K/yr

Lead AI image recognition and computer vision strategies for infrastructure asset data extraction assessing model approaches, overseeing implementation, and validating outputs against domain ...

Citian

AI Integration Engineer

Washington, DC · On-site

$117K - $158K/yr

... Lead AI image recognition and computer vision strategies for infrastructure asset data extraction assessing model approaches, overseeing implementation, and validating outputs against domain ...

Citian

AI Integration Engineer

Washington, DC

$117K - $158K/yr

Lead AI image recognition and computer vision strategies for infrastructure asset data extraction assessing model approaches, overseeing implementation, and validating outputs against domain ...

Citian

AI Integration Engineer

Washington, DC · On-site

$117K - $158K/yr

Lead AI image recognition and computer vision strategies for infrastructure asset data extraction assessing model approaches, overseeing implementation, and validating outputs against domain ...

Hatch IT

Image & Computer Vision AI Engineer

Reston, VA · On-site

$140K - $170K/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 ...

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 ...

CoverMyMeds

Senior AI Full stack Software Engineer

Columbus, OH · On-site

$118K - $156K/yr

They are seeking a Senior AI Full Stack Software Engineer to design, develop, and deploy AI-powered ... Build scalable systems that incorporate LLMs, voice/image recognition, and document parsing into ...

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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 Aug 5, 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.
More about Ai Image Recognition jobs
What cities are hiring for Ai Image Recognition jobs? Cities with the most Ai Image Recognition job openings:
What states have the most Ai Image Recognition jobs? States with the most job openings for Ai Image Recognition jobs include:
What job categories do people searching Ai Image Recognition jobs look for? The top searched job categories for Ai Image Recognition jobs are:
Ai Image Recognition jobs near you
Infographic showing various Ai Image Recognition job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 20% Part Time, and 7% Contract. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $95,090 per year, or $45.7 per hour.

AI Integration Engineer

Citian

Washington, DC

$117K - $158K/yr

Other

Re-posted 24 days ago

Job description

Who You Are:

As an AI Integration Engineer at Citian, you'll lead efforts incorporating AI into our products, bridging civil engineering domain knowledge with practical AI implementation. You will work alongside our Engineering, Data, and Research teams to build scalable processes and find solutions to improve our data integrity.  You will be expected to prototype ideas, assess third-party tools and models, and translate technical findings into actionable product decisions. You are resourceful, innovative, and continuously seek opportunities to improve processes and drive efficiency. Your strong communication and collaboration skills enable you to work effectively with cross-functional teams and stakeholders. If you are passionate about applied AI Engineering and are eager to contribute to the success of a startup, we would love to hear from you.

Expected Duties:

  • Serve as the domain bridge between civil/transportation engineering knowledge and AI capabilities, evaluating whether AI outputs meet real-world infrastructure standards and directing the team accordingly.
  • You will help to balance product strategy and research by working with our research team on prompting techniques, model capabilities, domain specific finetuning
  • Help lead our efforts to get models to perform how we want them to, including enabling models with tool use and other techniques to get the best out of the LLMs.
  • Work closely with our Data team and specific datasets that can be used for continued pre-training, RLHF, in-context-learning (ICL), and other applications.
  • Lead AI image recognition and computer vision strategies for infrastructure asset data extraction assessing model approaches, overseeing implementation, and validating outputs against domain benchmarks.
  • Contribute to fine-tuning strategy for transportation/infrastructure-specific models by collaborating with the research team on domain adaptation, benchmarking, and model evaluation.
  • Evaluate and recommend third-party AI tools, APIs, and foundation models relevant to Citian's use cases, balancing build vs. buy tradeoffs in coordination with Engineering.
  • Own and manage the application of AI to QA/QC processes; directing strategy, evaluating outputs for domain accuracy, and iterating with the Data team to continuously improve data quality and integrity.

Required Skills & Experience:

  • Bachelor's in Computer Science, Data Science, or related field
  • 5+ years of professional experience through work or personal projects
  • 3+ years of AI focused experience ideally within a product environment
  • Strong understanding of Computer Science topics such as optimization and algorithms
  • Understanding of Python/SQL code and ability to retrieve and store data safely through a back end
  • Familiarity with RESTful APIs and back-end concepts sufficient to prototype, test, and evaluate integrations. Hands-on implementation experience a plus but not required.
  • Experience with cloud services, specifically AWS, and the ability to leverage its features for scalable back-end AI solutions is highly desired. (S3, Lambda Functions)
  • Experience with computer vision or AI image recognition applications, even at a prototyping or evaluation level.
  • Meaningful exposure to civil engineering, transportation infrastructure, or geospatial data, sufficient to critically evaluate AI outputs in these domains and communicate credibly with domain experts.
  • Capacity to communicate solutions with teammates

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