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Computer Vision Scientist Jobs in Texas (NOW HIRING)

T3i, Inc.

Computer Vision Engineer - UAS

San Antonio, TX

$100K - $118K/yr

Bachelor's degree in Computer Science, Electrical Engineering, Robotics, Applied Math, or related field * 5+ years of hands-on experience developing and deploying computer vision systems (3+ years ...

Darbytek

Sr. Computer Vision Engineer

Austin, TX · On-site

$180K - $250K/yr

At least a master's degree in computer science, Electrical Engineering, or a related field, with a strong focus on machine learning and computer vision. * 9+ years of experience working on machine ...

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All JobsComputer Vision Scientist JobsComputer Vision Scientist Jobs in Texas

Computer Vision Scientist information

See Texas salary details

$47K

$103.7K

$128.1K

How much do computer vision scientist jobs pay per year?

As of Jun 23, 2026, the average yearly pay for computer vision scientist in Texas is $103,733.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,000.00 and $127,600.00 per year, depending on experience, location, and employer.

What is the difference between Computer Vision Scientist vs Machine Learning Engineer?

AspectComputer Vision ScientistMachine Learning Engineer
Required CredentialsMaster's or PhD in Computer Science, AI, or related fieldsBachelor's or Master's in Computer Science, Software Engineering, or related fields
Work EnvironmentResearch labs, R&D departments, academiaProduct teams, software development environments
Industry UsageDeveloping algorithms for image/video analysis, object detectionBuilding scalable ML models for various applications including vision

While both roles involve machine learning, Computer Vision Scientists focus on developing algorithms specifically for visual data, whereas Machine Learning Engineers implement and deploy these models in real-world applications. The roles often overlap but differ mainly in their primary focus and work environment.

What are the key skills and qualifications needed to thrive as a Computer Vision Scientist, and why are they important?

A Computer Vision Scientist needs a strong background in mathematics, machine learning, and image processing, often supported by a graduate degree in computer science or a related field. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), programming languages like Python or C++, and experience with libraries like OpenCV are typically required. Creative problem-solving, critical thinking, and effective communication help distinguish top performers in this role. These skills are essential for developing innovative computer vision solutions that can be effectively integrated into real-world applications.

What are some common challenges faced by Computer Vision Scientists when deploying models to production environments?

Computer Vision Scientists often encounter challenges such as ensuring model robustness under varying real-world conditions, optimizing inference speed for deployment on resource-constrained devices, and managing large-scale data for continuous model improvement. Collaboration with engineering teams is crucial to integrate models efficiently into existing software pipelines and to address issues like latency and scalability. Additionally, maintaining high accuracy while minimizing false positives and negatives in live environments requires ongoing monitoring and iterative improvement.

What are Computer Vision Scientists?

Computer Vision Scientists are professionals who develop algorithms and models that allow computers to interpret and understand visual information from the world, such as images and videos. They use techniques from machine learning, artificial intelligence, and image processing to solve problems like object detection, facial recognition, and scene understanding. Their work is essential in fields such as autonomous vehicles, healthcare imaging, robotics, and augmented reality. Computer Vision Scientists often collaborate with engineers and domain experts to create practical applications and improve existing technologies.
What are popular job titles related to Computer Vision Scientist jobs in Texas? For Computer Vision Scientist jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Computer Vision Scientist jobs in Texas look for? The top searched job categories for Computer Vision Scientist jobs in Texas are:
What cities in Texas are hiring for Computer Vision Scientist jobs? Cities in Texas with the most Computer Vision Scientist job openings:
Computer Vision Scientist jobs near you
Infographic showing various Computer Vision Scientist job openings in Texas as of June 2026, with employment types broken down into 38% Full Time, 43% Part Time, 2% Temporary, and 17% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $103,733 per year, or $49.9 per hour.

Computer Vision Engineer

Texas State Library and Archives Commision

Richardson, TX • On-site

$101K - $119K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

  • MS/PhD in computer science, or related technical disciplines.
  • 6+ years hands-on development experience in deep learning/machine learning/data science with expertise in computer vision.
  • Proficient in Python programming language.
  • Solid knowledge of machine learning frameworks and tools - PyTorch, OpenVino, TensorRT, OpenCV, NumPy etc.
  • Solid knowledge of developing convolution neural networks from scratch.
  • Experience with object detection, segmentation, classification and object tracking.
  • Experience with handling and manipulating large datasets.
  • Experience with developing automated machine learning pipelines.
  • Solid experience in building scalable, high performance software systems.
  • Proven ability to translate high-level product requirements into technical solutions.
  • Enthusiasm to work in a vibrant, collaborative and fast-paced engineering team.

Resource should be working in the office, Work from home is not supported.

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