Computer Vision Engineer Internships
Computer vision engineer internships give university students, recent graduates, and early-career switchers hands-on project experience building and deploying real vision systems, mentorship from working engineers, and, at many employers, a path toward a full-time offer. Openings are concentrated across {{top_industries_phrase}}, with Meta, KLA, and Mill among the employers posting roles now.
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Research Scientist Intern, Computer Vision - Video Intelligence (PhD) Responsibilities:
- Conduct research on advanced topics in video generation and understanding, including but not limited to text-to-video generative models, image-to-video generative models, video understanding models, unified native video generative models.
- Design, implement, and evaluate novel algorithms and model architectures.
- Collaborate closely with researchers and engineers across the Video Intelligence group and broader GenAI teams.
- Contribute to publications in top-tier conferences and journals in AI, computer vision, and machine learning.
- Present findings and share insights that help shape both ongoing research and future directions.
Minimum Qualifications:
- Programming experience in Python and hands-on experience in deep learning frameworks such as PyTorch
- Experience working on generative models e.g. diffusion models, LLM, autoregressive transformers, etc
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Preferred Qualifications:
- Proven track record of solid research achievements as demonstrated by grants, fellowships, patents, as well as publications at leading AI conferences such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, or SIGGRAPH
- Strong track record of contributions to open-source projects, benchmarks, or shared research artifacts
- Research experience in video generation, temporal modeling, multimodal learning or unified native video generative models
- Experience working and communicating cross functionally in a fast-paced team environment. Ideal candidates should have the ability to quickly understand and identify the research opportunities behind real-world applications, select the appropriate ML methods to explore, and proactively drive the iterations based on clear analysis of the current results
About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$7,650/month to $12,667/month + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
Research Scientist Intern, Computer Vision - Video Intelligence (PhD) Responsibilities:
- Conduct research on advanced topics in video generation and understanding, including but not limited to text-to-video generative models, image-to-video generative models, video understanding models, unified native video generative models.
- Design, implement, and evaluate novel algorithms and model architectures.
- Collaborate closely with researchers and engineers across the Video Intelligence group and broader GenAI teams.
- Contribute to publications in top-tier conferences and journals in AI, computer vision, and machine learning.
- Present findings and share insights that help shape both ongoing research and future directions.
Minimum Qualifications:
- Programming experience in Python and hands-on experience in deep learning frameworks such as PyTorch
- Experience working on generative models e.g. diffusion models, LLM, autoregressive transformers, etc
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Preferred Qualifications:
- Proven track record of solid research achievements as demonstrated by grants, fellowships, patents, as well as publications at leading AI conferences such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, or SIGGRAPH
- Strong track record of contributions to open-source projects, benchmarks, or shared research artifacts
- Research experience in video generation, temporal modeling, multimodal learning or unified native video generative models
- Experience working and communicating cross functionally in a fast-paced team environment. Ideal candidates should have the ability to quickly understand and identify the research opportunities behind real-world applications, select the appropriate ML methods to explore, and proactively drive the iterations based on clear analysis of the current results
About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$7,650/month to $12,667/month + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
Computer Vision Engineer Internship Market
Who's Hiring
Tips for Your Computer Vision Engineer Internship Search
Apply to summer roles in the fall
Large employers, particularly in tech and defense, recruit summer computer vision engineer interns the preceding fall and close cohorts months before the start date. Smaller companies and co-op programs post closer to their actual start dates, so check for openings year-round rather than waiting until spring.
Build a portfolio before you apply
Hiring teams for computer vision engineer interns evaluate project work, not job history. Complete two or three documented projects, commit clean code to a public repository, and write up what problem you solved and how. A strong GitHub profile or project write-up gives recruiters something concrete to assess when your resume is light on experience.
Work your campus network and apply directly
Campus career fairs surface structured programs tied to your university, and professors or career center staff often know which employers recruit from your school before roles appear publicly. Applying directly to companies running smaller cohorts alongside campus activity widens the pool you can reach with a single job-search effort.
Practice your technical screen out loud
Computer vision engineer intern interviews typically include a coding screen covering data structures, algorithms, and applied machine learning or image processing problems. Practice solving problems out loud and explaining your reasoning step by step, since interviewers weigh how you think through a problem as much as whether you reach the correct answer.
Target structured internship programs early
Larger employers in robotics, autonomous systems, and computer vision research run cohort or university-partner programs designed to train candidates new to applied vision work. These programs recruit in the first wave of hiring each cycle and fill fast, so identify the ones that fit your background and submit applications as soon as they open.
Set your work-type filter before you start
On-site roles are 0% of the computer vision engineer internships listed here. Decide what you can realistically commit to, whether on-site, hybrid, or remote, before you start reviewing listings. Filtering by location and work type upfront means you spend time on roles you can actually accept.
Computer Vision Engineer Internships: Frequently Asked Questions
How do I get a computer vision engineer internship?
Lead with coursework and personal projects rather than work history, since hiring teams expect limited experience at the intern level. A portfolio with documented computer vision projects, linked code repositories, and clear write-ups of your methodology gives recruiters something concrete to assess. Combine direct applications with campus career fairs, where recruiters often move faster for students they meet in person.
Can a computer vision engineer internship turn into a full-time job?
Many employers extend return offers to strong interns, but conversion is never guaranteed. What drives it for computer vision engineer interns is consistent delivery on real project work, available headcount on the team, and understanding the return-offer timeline before your internship ends. Position for one by treating every assignment seriously without counting on an offer materializing.
When should I apply for computer vision engineer internships?
Earlier than most expect. Large tech and defense employers recruit summer interns the preceding fall, often closing cohorts before spring semester begins. Smaller companies and co-op programs post closer to start dates, so openings appear year-round. Checking regularly and applying as soon as a role fits your background is the most reliable approach.
Are computer vision engineer internships paid?
Most professional computer vision engineer internships in the U.S. are paid. Compensation varies by company size, industry, and location. Where an employer discloses pay, listings show it directly so you can factor it into your decision without having to ask upfront.
What should a computer vision engineer internship resume include?
Lead with two or three complete, documented projects rather than work history. For each, name the tools and frameworks used, the problem you solved, and link to the code repository or published write-up so reviewers can assess your actual work. Add relevant coursework in computer vision, machine learning, and linear algebra, and keep the whole document to one page.
Are there remote computer vision engineer internships?
Yes. Remote and hybrid roles make up 100% of the computer vision engineer internship listings here, with the rest on-site. Remote cohorts fill fast because they draw applicants nationally, so apply early and filter by work type to see available options before they close.
Can international students get computer vision engineer internships?
Yes. F-1 students can intern through CPT while enrolled or through OPT work authorization after finishing a degree, and the employer does not have to file anything for either, so many companies are open to international interns. Confirm your eligibility and timing with your university's international student office before accepting an offer.
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