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Full Time Computer Vision Postdoc Jobs (NOW HIRING)

XPENG

Senior Computer Vision Engineer

Santa Clara, CA · On-site

$143.90K - $189.70K/yr

We are seeking a talented Computer Vision / Machine Learning Engineer to join our global team. In ... The base salary range for this full-time position is $174,720 - $295,680 in addition to bonus ...

Corning

Sr. Computer Vision Engineer

Painted Post, NY

$89.13K - $122.56K/yr

Scope of Position: A Sr. Computer Vision engineering position in the Corning Environmental ... The range for this position is $89,134.00 - $122,559.00 assuming full time status. Starting pay for ...

Verkada

Software Engineer - Computer Vision

San Mateo, CA · On-site

$180K - $300K/yr

About the Role At the forefront of innovation, the Computer Vision team develops the artificial ... full-time employees for this position, comprised of base compensation and commissions (if ...

Berkely Lab

Postdoctoral Scholar

San Francisco, CA · On-site

... (3) computer vision for extracting complex patterns, structure, and meaning from images and/or ... This is a full-time, 2 year, postdoctoral appointment with the possibility of renewal based upon ...

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Full Time Computer Vision Postdoc information

What are the key skills and qualifications needed to thrive as a Full Time Computer Vision Postdoc, and why are they important?

To thrive as a Full Time Computer Vision Postdoc, you need a strong background in computer vision, machine learning, and mathematical modeling, typically supported by a PhD in computer science, engineering, or a related field. Experience with programming languages such as Python or C++, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with version control and high-performance computing environments are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication are crucial for collaborating with interdisciplinary teams and publishing research findings. These skills ensure the ability to drive innovative research, contribute to scientific advancements, and meet the rigorous demands of academic or industry research environments.

What are some common challenges faced by a Full Time Computer Vision Postdoc working in a research setting?

As a Full Time Computer Vision Postdoc, you may encounter challenges such as balancing independent research with collaborative projects, staying current with rapid advancements in machine learning techniques, and managing the publication process for top-tier conferences and journals. Additionally, you'll often need to adapt your work to align with the broader goals of your research group or funding body. Effective communication and teamwork are essential, as you'll likely collaborate with other researchers, engineers, and sometimes industry partners to push the boundaries of computer vision applications.

What is a Full Time Computer Vision Postdoc?

A Full Time Computer Vision Postdoc is a researcher who has completed their PhD and works full time on advanced research projects involving computer vision. This role typically involves developing new algorithms, conducting experiments, publishing papers, and collaborating with other scientists in areas such as image recognition, object detection, and machine learning. Postdocs often work at universities, research institutes, or tech companies, and their work helps drive innovation in fields like robotics, healthcare, and autonomous vehicles. The position is generally temporary, lasting from one to three years, and is designed to build expertise before pursuing more permanent academic or industry roles.
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Infographic showing various Full Time Computer Vision Postdoc job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 92% In-person, and 8% Remote job distribution.

Senior Computer Vision Engineer

XPENG

Santa Clara, CA • On-site

$143.90K - $189.70K/yr

Full-time

Posted 11 days ago

Job description

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.
We are seeking a talented Computer Vision / Machine Learning Engineer to join our global team. In this role, you will develop and optimize multi-modal models and computer vision systems, driving performance, efficiency, and real-world deployment. The ideal candidate has hands-on experience with multi-modal model training and optimization, a strong foundation in computer vision, and solid C++ engineering skills.
Key Responsibilities
  • Research and implement multi-modal large models (image-text, image-audio, etc.) training, fine-tuning, and inference optimization strategies, continuously improving model performance, efficiency, and generalization ability.
  • Design and optimize computer vision models and algorithms (e.g., detection, classification, segmentation, feature extraction) to support real-world applications.
  • Collaborate with cross-functional teams (product, engineering, data) to translate research into scalable, reliable, and production-ready solutions.
  • Use C++ to implement and optimize models and systems, including deployment, performance tuning, and integration, ensuring low latency and high throughput.
  • Stay up to date with advances in computer vision and multi-modal AI, and apply new methods to improve model performance and product impact.
  • Contribute to technical discussions, code reviews, and knowledge sharing to improve code quality and engineering best practices.
Minimum Qualifications
  • Master's or Ph.D. in Computer Science or a related field, with strong expertise in computer vision and machine learning.
  • 1-3 years of experience in multi-modal large model training, fine-tuning, and optimization (e.g., CLIP, Flamingo, BLIP, or self-developed multi-modal models), with a deep understanding of multi-modal fusion mechanisms.
  • Strong foundation in computer vision, including object detection, image classification, feature matching, and image enhancement.
  • Strong C++ development skills, with proficiency in STL, multi-threading, memory management, and performance optimization; experience in production-level implementation and deployment is required.
  • Familiar with deep learning frameworks (e.g., PyTorch, TensorFlow) and computer vision libraries (e.g., OpenCV, OpenMMLab).
  • Strong problem-solving ability, self-driven, and passionate about technological innovation; ability to work independently and in a team.
Preferred Qualifications
  • Experience in edge device algorithm deployment, published papers in top computer vision conferences (CVPR, ICCV, ECCV), or open-source project contributions in related fields.
What do we provide:
  • A fun, supportive and engaging environment.
  • Opportunity to make a significant impact on the transportation revolution by the means of advancing autonomous driving.
  • Opportunity to work on cutting edge technologies with the top talent in the field.
  • Competitive compensation package.
  • Snacks, lunches and fun activities.

The base salary range for this full-time position is $174,720 - $295,680 in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.

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