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Computer Vision Scientist Jobs in Houston, TX (NOW HIRING)

Talentry, LLC

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Machine Learning Guru (Autonomous Navigation)**

Houston, TX · Remote

$200K - $300K/yr

D. or Master's) in computer science, computer engineering, mathematics, physics, or related field. * In-depth knowledge and experience in machine learning and/or computer vision, employing bleeding ...

Staffingine LLC

Drone Data Engineer

Houston, TX · On-site

$109K - $131K/yr

Computer vision models * Defect detection * Asset condition monitoring * Digital twin platforms * Work closely with data science teams to operationalize AI models on drone data * Systems Cloud ...

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All JobsComputer Vision Scientist JobsComputer Vision Scientist Jobs in Houston, TX

Computer Vision Scientist information

See Houston, TX salary details

$48.2K

$106.3K

$131.3K

How much do computer vision scientist jobs pay per year?

As of Aug 3, 2026, the average yearly pay for computer vision scientist in Houston, TX is $106,329.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,200.00 and $130,800.00 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 Houston, TX? For Computer Vision Scientist jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Computer Vision Scientist jobs in Houston, TX look for? The top searched job categories for Computer Vision Scientist jobs in Houston, TX are:
Computer Vision Scientist jobs near you
Infographic showing various Computer Vision Scientist job openings in Houston, TX as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $106,329 per year, or $51.1 per hour.

Algorithm Engineer, Deep Learning & Vision (New Grad)

Bot Auto

Houston, TX • On-site

Full-time

Posted 7 days ago

Job description

Company Introduction
At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.
Key Responsibilities
  • Model Implementation & Iteration: Participate in the development, training, and optimization of state-of-the-art deep learning models for autonomous driving, with a focus on end-to-end architectures, including perception, online mapping, and end-to-end planning.
  • Full Lifecycle Execution: Engage in the entire machine learning workflow under the guidance of domain experts, spanning from data curation and data analysis to model experimentation, hyperparameter tuning, and rigorous performance metric verification.
  • Cross-Functional Collaboration: Partner with simulation, infrastructure, and downstream planning/control teams to deploy, evaluate, and integrate machine learning components into our production pipeline for autonomous trucks.
  • Literature Tracking: Stay abreast of the latest research breakthroughs in computer vision and generative AI, and actively bench-test promising SOTA methods to solve real-world corner cases.
How You'll Grow
This matters as much to us as what you'll ship.
  • You get a real mentor. Every engineer is paired with senior-level engineers developing you. Mentorship here is weighted toward design and judgment: how to frame a problem, what to build and why, how to tell whether a solution is actually right.
  • We promote fast. Managers are expected to push engineers to attempt work above their current level, and to promote in the next cycle when they deliver it.
Qualifications
Required:
  • Education: A Bachelor's, Master's, or Ph.D. (including upcoming graduates) in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, Physics, or a related quantitative field.
  • You have trained neural networks. Coursework, research, personal projects, open-source work, and internships all count. We care that you have actually run the loop: built a model, trained it, found out why it was not working, and fixed it.
  • Core Knowledge: Strong theoretical foundation in machine learning and deep learning, with a solid understanding of modern architectures (e.g., Transformers, CNNs, Graphs).
  • Technical Stack: Proficiency in Python and deep learning frameworks such as PyTorch, along with strong software engineering fundamentals (data structures, algorithms, and clean coding practices).
  • Attributes: High self-motivation, strong analytical and problem-solving skills, a fast learner in a high-velocity startup environment, and a strong team-player mindset.
Preferred:
  • Computer vision. Research or projects in computer vision, and particularly in 3D.
  • Specific Research Directions: Academic thesis or deeply focused research experience in one or more of the following domains:
    • Computer Vision (2D or 3D)
    • Online Mapping, Vectorization, or Visual SLAM
    • Prediction and Behavioral Modeling
  • Academic Achievements: A track record of research publications in machine learning, computer vision, or robotics conferences/journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICRA, IROS).
  • Engineering Plus: Hands-on experience with model deployment, quantization, distillation, or inference acceleration tools (e.g., TensorRT, ONNX, CUDA, C++).
  • Industry Exposure: Prior internship experience within the autonomous driving industry or advanced robotics labs.

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