Computer Vision Engineer Jobs
Computer Vision Engineer jobs are open across automotive, robotics, healthcare, defense, and consumer tech, from new-grad to staff and principal levels, with specializations in object detection, 3D reconstruction, and autonomous systems. Find a role that fits from the openings below and apply directly.
Find Computer Vision Engineer JobsOverview
Showing 5 of 46+ Computer Vision Engineer jobs
INTRODUCTION
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!
ROLE AND RESPONSIBILITIES
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++).
BASIC QUALIFICATIONS
- 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.
PREFERRED QUALIFICATIONS
- 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 June 12, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.
JR2014050
INTRODUCTION
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!
ROLE AND RESPONSIBILITIES
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++).
BASIC QUALIFICATIONS
- 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.
PREFERRED QUALIFICATIONS
- 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 June 12, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.
JR2014050
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Find Computer Vision Engineer JobsComputer Vision Engineer Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Apple13
- Aquabyte3
- Meta3
- NVIDIA3
- Dexterity2
Top Industries Hiring
- Technology & Software19
- Electronics & Hardware15
- Banking & Financial Services5
- Construction & Real Estate3
- Consulting & Professional Services2
What Employers Look For
The qualifications that appear most often in computer vision engineer jobs.
- Proficiency in Python with deep learning frameworks such as PyTorch or TensorFlow
- Hands-on experience with OpenCV and classical image processing techniques
- Strong understanding of convolutional neural network architectures and object detection models
- Experience deploying models to production environments including cloud or edge hardware
- Familiarity with 3D vision techniques such as point cloud processing or stereo depth estimation
- Bachelor's or master's degree in computer science, electrical engineering, or a related field
Tips for Your Computer Vision Engineer Job Search
Quantify your model performance results
Hiring managers want numbers, not descriptions. Replace 'improved detection accuracy' with the exact mAP score, inference latency reduction, or false-positive rate you achieved. Reviewers skim resumes fast, and concrete metrics on real datasets make your work immediately credible.
Tailor your GitHub to each application
Pin repositories that match the stack in the job description. If a role emphasizes real-time edge inference, push your TensorRT or ONNX runtime project to the top. Reviewers often check GitHub before the phone screen, so alignment there can determine whether you advance.
Apply early to roles that fit
Migrate Mate lists computer vision engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target job descriptions by deployment environment
Cloud-hosted pipeline roles and embedded edge-device roles call for different skills. Read postings carefully for keywords like CUDA, OpenVINO, or FPGA to distinguish them. Applying to roles that match your actual deployment experience dramatically improves your callback rate.
Prepare a live demo for technical screens
Many computer vision interview loops include a take-home or live coding task involving image processing or model inference. Practice explaining your architectural choices out loud, not just writing code. Interviewers weigh your reasoning as heavily as your solution.
Negotiate using competing offer timelines
If you have multiple interviews in flight, coordinate your offer deadlines before any explode. Letting a hiring team know you have another process moving forward is standard and often accelerates their decision. Use that window to request additional time or a competing offer match.
Computer Vision Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most computer vision engineers?
The companies hiring the most computer vision engineers right now include Apple, Aquabyte, and Meta, with the largest share of openings in California, Texas, and Washington, based on current listings on Migrate Mate as of June 2026. Automotive, defense, and consumer robotics employers tend to post the highest volumes of these roles.
How many computer vision engineer jobs are remote?
About 11% of computer vision engineer openings are fully remote or hybrid as of June 2026, making it a more location-flexible field than many hardware-adjacent engineering disciplines. Research-focused and cloud-pipeline roles tend to be the most remote-friendly, while positions involving physical cameras, robots, or embedded systems typically require on-site presence.
How do you become a computer vision engineer?
Start by building a strong foundation in linear algebra, calculus, and probability, then learn Python alongside a deep learning framework such as PyTorch. Work through publicly available datasets like COCO or ImageNet to build hands-on experience with detection and segmentation pipelines. Complete projects you can publish to GitHub, contribute to open-source vision libraries, and apply to entry-level or internship roles that involve real deployment work.
Can you get hired as a computer vision engineer without much experience?
Yes, but your portfolio has to substitute for work history. Build end-to-end projects that go beyond notebook tutorials, such as a deployable object detection app or a real-time inference pipeline running on your own hardware. Open-source contributions, Kaggle competition placements in vision tracks, and published research, even preprints, all signal practical ability to hiring teams evaluating candidates without a professional resume.
What does the computer vision engineer interview process look like?
Most processes include an initial recruiter call, a technical phone screen covering Python and deep learning fundamentals, and a multi-stage loop with a take-home or live coding task focused on image processing or model evaluation. Later rounds typically involve a system design discussion around vision pipelines at scale and a cross-functional presentation where you walk through a past project in detail. Some roles add a paper review or research discussion.
Where can I find and apply to computer vision engineer jobs?
You can find and apply to computer vision engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your background and specialization, then apply directly to each one that fits.
See All 46+ Computer Vision Engineer Jobs
Jump back to the full list of openings and apply to any computer vision engineer role that fits.
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