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.
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Showing 5 of 106+ Computer Vision Engineer jobs
Minimum qualifications:
- Bachelor’s degree, or equivalent practical experience.
- 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 5 years of experience in a technical leadership role; overseeing projects, with 3 years of experience in a people management, supervision/team leadership role.
- 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Experience with computer vision learning techniques, machine learning algorithms (supervised and unsupervised learning, deep learning, reinforcement learning), generative AI, or applied AI applications
Preferred qualifications:
- Master's degree or PhD in Computer Science, or a related technical field.
- 5 years of experience with one or more of the following: Computer Vision, Reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- Multiple research publications in top CV/ML conferences (e.g., CVPR/ICCV/ECCV/NIPS/ICLR).
- Experience working in large-sized engineering and cross-functional teams.
- Expertise in modeling with TensorFlow, JAX, etc.
- Excellent people management and communication skills.
About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
As an Engineering Manager, you will use your extensive Machine Learning and Computer Vision experience to lead the team in designing and building the freshest and most detailed 3D navigation map using sensor data (e.g., imagery, vehicle telemetry, location data, authoritative data, etc.), large ML models, and AI techniques to create new structured geospatial data and transformative user experiences for 2 billion+ users globally.
The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving complex computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Take end-to-end ownership of converting complex imagery, location, and sensor data into precise geometries to power Geo’s next generation navigation products. Translate ambiguous input data challenges into clear algorithmic, ML, GenAI formulations, brainstorming directly with product, UX, and engineering to define the optimal visual experience and iterate towards scalable solutions.
- Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
- Set clear expectations with individuals based on their level and role, aligned with broader organizational goals. Meet regularly with individuals to discuss performance, development, feedback and coaching.
- Develop the long-term technical outlook and roadmap, meeting anticipated future requirements and infrastructure needs.
- Design, guide and vet system designs, and write product or system development code to solve ambiguous problems. Conduct code reviews and provide feedback ensuring best practices.
Minimum qualifications:
- Bachelor’s degree, or equivalent practical experience.
- 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 5 years of experience in a technical leadership role; overseeing projects, with 3 years of experience in a people management, supervision/team leadership role.
- 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Experience with computer vision learning techniques, machine learning algorithms (supervised and unsupervised learning, deep learning, reinforcement learning), generative AI, or applied AI applications
Preferred qualifications:
- Master's degree or PhD in Computer Science, or a related technical field.
- 5 years of experience with one or more of the following: Computer Vision, Reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- Multiple research publications in top CV/ML conferences (e.g., CVPR/ICCV/ECCV/NIPS/ICLR).
- Experience working in large-sized engineering and cross-functional teams.
- Expertise in modeling with TensorFlow, JAX, etc.
- Excellent people management and communication skills.
About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
As an Engineering Manager, you will use your extensive Machine Learning and Computer Vision experience to lead the team in designing and building the freshest and most detailed 3D navigation map using sensor data (e.g., imagery, vehicle telemetry, location data, authoritative data, etc.), large ML models, and AI techniques to create new structured geospatial data and transformative user experiences for 2 billion+ users globally.
The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving complex computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Take end-to-end ownership of converting complex imagery, location, and sensor data into precise geometries to power Geo’s next generation navigation products. Translate ambiguous input data challenges into clear algorithmic, ML, GenAI formulations, brainstorming directly with product, UX, and engineering to define the optimal visual experience and iterate towards scalable solutions.
- Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
- Set clear expectations with individuals based on their level and role, aligned with broader organizational goals. Meet regularly with individuals to discuss performance, development, feedback and coaching.
- Develop the long-term technical outlook and roadmap, meeting anticipated future requirements and infrastructure needs.
- Design, guide and vet system designs, and write product or system development code to solve ambiguous problems. Conduct code reviews and provide feedback ensuring best practices.
Computer Vision Engineer Jobs by Experience Level
See All 106+ Computer Vision Engineer Jobs
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Find Computer Vision Engineer JobsComputer Vision Engineer Job Market
Who's Hiring
Top Industries Hiring
- Consulting & Professional Services
- Electronics & Hardware
- Technology & Software
- Automotive
- Telecommunications
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, Meta, and Google, with the largest share of openings in California, New York, and Washington, based on current listings on Migrate Mate as of September 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 35% of computer vision engineer openings are fully remote or hybrid as of September 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 106+ Computer Vision Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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