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Entry Level Computer Vision Deep Learning Engineer Jobs in Houston, TX

Bot Auto

Intern, Deep Learning Engineer

Houston, TX · On-site

$14.25 - $19/hr

... Deep Learning, Computer Vision, Robotics, or related fields. * Technical Stack: Proficient in ... Engineering Plus: Experience with Linux, Git, C++, or deployment tools like TensorRT/ONNX.

Bot Auto

Intern, Deep Learning Engineer

Houston, TX · On-site

$14.25 - $19/hr

... Deep Learning, Computer Vision, Robotics, or related fields. * Technical Stack: Proficient in ... Engineering Plus: Experience with Linux, Git, C++, or deployment tools like TensorRT/ONNX.

ResolveTech Solutions Inc.

CAD Technician I

Houston, TX · On-site

... entry-level CAD Technician I to create detailed technical drawings for building, architectural, structural, and civil engineering projects. The ideal candidate should have basic knowledge of CAD ...

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Entry Level Computer Vision Deep Learning Engineer information

See Houston, TX salary details

$46.3K

$116K

$131.3K

How much do entry level computer vision deep learning engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for entry level computer vision deep learning engineer in Houston, TX is $116,044.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,500.00 and $125,600.00 per year, depending on experience, location, and employer.

What does an entry level computer vision deep learning engineer do?

An Entry Level Computer Vision Deep Learning Engineer works on developing and implementing algorithms that allow computers to interpret and understand visual information from the world, such as images or videos. They typically use deep learning techniques, especially neural networks, to build models for tasks like object detection, facial recognition, and image classification. Their responsibilities may include data preprocessing, model training and evaluation, writing code (often in Python), and collaborating with senior engineers on real-world projects. This role is ideal for those who have a strong foundation in machine learning, programming, and mathematics, but are just starting their careers in the field.

What types of projects do entry level computer vision deep learning engineers typically work on, and how is their work structured within a team?

As an entry-level Computer Vision Deep Learning Engineer, you can expect to contribute to projects like object detection, image classification, and model optimization for real-world applications. Your tasks may include data preprocessing, training and evaluating neural networks, and writing code to integrate models into products or pipelines. You'll often collaborate closely with senior engineers, data scientists, and product managers, typically working in agile teams where regular code reviews and knowledge sharing are common. This collaborative environment not only helps you learn best practices but also provides opportunities to gradually take on more responsibility as your skills develop.

What are the key skills and qualifications needed to thrive as an entry level computer vision deep learning engineer, and why are they important?

To thrive as an Entry Level Computer Vision Deep Learning Engineer, you need a solid understanding of computer vision fundamentals, deep learning concepts, and programming skills in languages like Python, along with a relevant degree in computer science, engineering, or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience with OpenCV, and knowledge of version control systems like Git are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate within teams and tackle complex challenges. These skills and qualities are crucial for developing, deploying, and optimizing computer vision solutions that meet real-world business needs.

What are the most commonly searched types of Computer Vision Deep Learning Engineer jobs in Houston, TX?

The most popular types of Computer Vision Deep Learning Engineer jobs in Houston, TX are:

What are popular job titles related to Entry Level Computer Vision Deep Learning Engineer jobs in Houston, TX?

For Entry Level Computer Vision Deep Learning Engineer jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Entry Level Computer Vision Deep Learning Engineer jobs in Houston, TX look for?

The top searched job categories for Entry Level Computer Vision Deep Learning Engineer jobs in Houston, TX are:

What cities near Houston, TX are hiring for Entry Level Computer Vision Deep Learning Engineer jobs?

Cities near Houston, TX with the most Entry Level Computer Vision Deep Learning Engineer job openings:

Entry Level Computer Vision Deep Learning Engineer jobs near you
Infographic showing various Entry Level Computer Vision Deep Learning Engineer job openings in Houston, TX as of June 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $116,044 per year, or $55.8 per hour.

Algorithm Engineer, Deep Learning & Vision (New Grad)

Houston, TX • On-site

Bot Auto
See more jobs at Bot Autoexternal

Full-time

Re-posted 14 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.
QualificationsRequired:
  • 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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