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Computer Vision Deep Learning Jobs (NOW HIRING)

Computer Vision and Machine Learning Engineer

Sunnyvale, CA ยท On-site

$130.90K - $154.30K/yr

We seek a driven and dedicated engineer with deep expertise in computer vision and deep learning. As a member of our dynamic team, you will have the unique and rewarding opportunity to influence next ...

Computer Vision and Machine Learning Engineer

Sunnyvale, CA ยท On-site

$130.90K - $154.30K/yr

We seek a driven and dedicated engineer with deep expertise in computer vision and deep learning. As a member of our dynamic team, you will have the unique and rewarding opportunity to influence next ...

Computer Vision/ AI Intern- R&D Summer 2026

Troy, MI ยท On-site

$14.25 - $19/hr

We seek a self-motivated intern to support our research team in projects focused on Computer Vision, Deep Learning, Image segmentation, and Pose estimation to contribute to new technology development ...

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Computer Vision Deep Learning information

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$33.5K

$48.3K

$63.5K

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

As of May 31, 2026, the average yearly pay for computer vision deep learning in the United States is $48,298.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,000.00 and $55,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Computer Vision Deep Learning Engineer, you need a strong background in mathematics, programming (especially Python), and deep learning concepts, often supported by a degree in computer science or a related field. Proficiency with frameworks like TensorFlow, PyTorch, OpenCV, and experience using GPU computing are highly valued, along with relevant certifications in machine learning or artificial intelligence. Strong analytical thinking, creative problem-solving, and effective communication skills set top candidates apart in this role. These competencies are essential for developing, optimizing, and deploying innovative computer vision solutions that address complex real-world challenges.

What are some common challenges faced in a Computer Vision Deep Learning role, and how can they be addressed?

Professionals in Computer Vision Deep Learning often face challenges such as managing large, complex datasets, ensuring high model accuracy, and dealing with real-world variability in images or video. Addressing these issues typically involves data augmentation, careful preprocessing, and the use of advanced architectures like CNNs and transformers. Collaboration with data engineers and domain experts is essential to ensure data quality and to tailor solutions to specific use cases. Additionally, staying updated with the latest research and tools can help in overcoming technical hurdles and enhancing model performance.

What is computer vision deep learning?

Computer vision deep learning is a field of artificial intelligence that leverages deep neural networks to enable computers to interpret and understand visual information from the world, such as images and videos. By using deep learning techniques, such as convolutional neural networks (CNNs), systems can perform tasks like image classification, object detection, and facial recognition with high accuracy. This technology is widely applied in industries including healthcare, automotive, and security for tasks ranging from medical image analysis to autonomous driving.

What is the difference between Computer Vision Deep Learning vs Computer Vision Engineer?

AspectComputer Vision Deep LearningComputer Vision Engineer
Required CredentialsBachelor's or higher in CS, AI, or related fields; knowledge of deep learning frameworksBachelor's or higher in CS or related fields; experience with computer vision algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on AI modelsSoftware development teams, product companies, tech firms applying computer vision
Employer & Industry UsageAI research, academia, companies developing deep learning models for vision tasksProduct development, application of computer vision in real-world projects

Computer Vision Deep Learning specialists focus on developing and applying deep learning models for visual data analysis, often involving research and model training. In contrast, Computer Vision Engineers implement and optimize computer vision algorithms within products and applications, emphasizing deployment and practical use. Both roles require a strong foundation in computer vision, but their focus areas and work environments differ.

More about Computer Vision Deep Learning jobs
Infographic showing various Computer Vision Deep Learning job openings in the United States as of May 2026, with employment types broken down into 2% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $48,298 per year, or $23.2 per hour.
Senior Deep Learning and Computer Vision Engineer - Autonomous Vehicles

Senior Deep Learning and Computer Vision Engineer - Autonomous Vehicles

Nvidia Corporation

Santa Clara, CA โ€ข On-site

Full-time

Posted 28 days ago


Job description

We are looking for a Deep Learning and Computer Vision engineer for our Autonomous Vehicles team. The role involves applying state-of-the-art techniques to build ground truth for autonomous vehicles, a critical aspect of our next-generation products. You will have the opportunity to work with top researchers and engineers in the field of deep learning and computer vision to deliver impact to our customers around the world. Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer a science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. The era of AI has begun. NVIDIA's GPUs run Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and AI come together in our architecture. This may explain why.
NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as "the AI company". Make your choice to join us today. We are training Deep Neural Networks for NVIDIA's Autonomous Vehicles effort, with the goal to enable autonomous driving. We are seeking Deep Learning/Machine Learning interns who are passionate about solving problems in perception, prediction, planning and control for self-driving cars to achieve full autonomy. Are you interested in inventing human level AI for navigation in the unconstrained world under any conditions? If so, join us!
What you'll be doing:
  • Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas.
  • Foster collaborative partnerships with our researchers and engineers, transforming innovative research into robust, industrial-strength machine learning models.
  • Taking approaches from initial evaluation and experimentation all the way to shipping.
  • Defining and collecting training datasets.
  • Building training pipelines and real-time inference run-times (PyTorch, TensorFlow, TensorRT, Python, C++).

What we need to see:
  • PhD with 1+ year, or MS (or equivalent experience) with 5+ years, of relevant experience in Computer Science, Computer Engineering, or a related technical field.
  • Proven experience building robust software.
  • Passionate about Artificial Intelligence for robotics and autonomous navigation
  • Strive to learn new things and like solving hard problems
  • Math knowledge
  • Experience in Deep Learning / Machine Learning. You have a background in Computer vision and/or Planning/Control.
  • Programming and debugging skills in C++ and/or Python.
  • Good communication and analytical skills. Ability to work with multiple teams in a dynamic environment.

Ways to stand out from the crowd:
  • Background in applying latest AI methods to solve Computer Vision and Autonomous Vehicles problems
  • Experience with Unsupervised or Self-supervised Learning
  • Involvement with architecture optimization, pruning, curriculum & multi-task training
  • Experience fusing data from different sensor modalities (e.g. Images and LIDAR data) to enable information conflation, label propagation, cross training.

We believe that realizing self-driving cars will be a defining contribution of our generation. We have the funding and scale, but we need your help. NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until March 21, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993