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Computer Vision Researcher Jobs in California (NOW HIRING)

Computer Vision & Machine Learning Engineer

Sunnyvale, CA ยท On-site

$130K - $154K/yr

The VCV org is a centralized applied research and engineering organization responsible for developing real-time on-device Computer Vision and Machine Perception technologies across Apple products. We ...

Junior Computer Vision Engineer

San Diego, CA ยท On-site

$100K - $200K/yr

Job Summary * - To research and develop scalable computer vision and machine learning solutions to a hard problem * - To investigate and solve exciting and difficult challenges of the real-world ...

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Computer Vision Researcher information

See California salary details

$29.6K

$111.6K

$162.3K

How much do computer vision researcher jobs pay per year?

As of Jul 9, 2026, the average yearly pay for computer vision researcher in California is $111,621.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,100.00 and $152,000.00 per year, depending on experience, location, and employer.

What does a Computer Vision Researcher do?

A Computer Vision Researcher develops algorithms and models that enable computers to interpret and understand visual information from the world, such as images and videos. They work on tasks like object detection, image segmentation, and facial recognition, often using techniques from machine learning and artificial intelligence. Their work is applied in fields such as autonomous vehicles, medical imaging, robotics, and augmented reality. Computer Vision Researchers typically conduct experiments, publish scientific papers, and collaborate with engineers to implement their findings in real-world applications.

What are some common challenges faced by Computer Vision Researchers when transitioning from theoretical research to practical applications?

Computer Vision Researchers often encounter challenges when moving from theoretical models to real-world deployment, such as dealing with noisy or incomplete data, ensuring scalability, and optimizing models for real-time performance. Collaborative work with software engineers and domain experts is crucial to address these issues and to adapt state-of-the-art algorithms for production environments. Additionally, staying updated with rapidly evolving tools and frameworks is essential for successfully bridging the gap between research and application.

What is the difference between Computer Vision Researcher vs Machine Learning Engineer?

AspectComputer Vision ResearcherMachine Learning Engineer
Required CredentialsMaster's or PhD in Computer Science, AI, or related fieldsBachelor's or Master's in Computer Science, Data Science, or related fields
Work EnvironmentResearch labs, academia, R&D departmentsTech companies, startups, product teams
Employer & Industry UsageUniversities, research institutions, AI-focused companiesTechnology firms, software companies, AI product development
Common Search & ComparisonYesYes

While both roles involve AI and machine learning, a Computer Vision Researcher primarily focuses on developing algorithms for visual data analysis and often works in research settings. In contrast, a Machine Learning Engineer applies machine learning techniques to build scalable AI products and solutions in industry environments.

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

To thrive as a Computer Vision Researcher, you need a strong background in mathematics, machine learning, image processing, and typically a graduate degree in computer science or a related field. Experience with deep learning frameworks (such as TensorFlow or PyTorch), programming languages (like Python or C++), and familiarity with relevant research publications are highly valued. Creativity, problem-solving abilities, and strong communication skills help researchers innovate and effectively share findings. These competencies are vital for advancing technology, developing novel algorithms, and collaborating within multidisciplinary teams.
What job categories do people searching Computer Vision Researcher jobs in California look for? The top searched job categories for Computer Vision Researcher jobs in California are:
Infographic showing various Computer Vision Researcher job openings in California as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, 1% Temporary, and 2% Contract. Highlights an 82% Physical, 1% Hybrid, and 17% Remote job distribution, with an average salary of $111,621 per year, or $53.7 per hour.

Research Scientist - Computer Vision

Epsilon Health

San Francisco, CA โ€ข On-site

Full-time

Posted 18 days ago


Job description

About Us
We're tackling one of healthcare's most critical challenges in medical imaging and diagnostics. Our company operates at the intersection of cutting-edge AI and clinical practice, building technology that directly impacts patient outcomes. We've assembled one of the industry's most comprehensive and diverse medical imaging datasets and have a proven product-market fit with a substantial customer pipeline already in place.
Role Overview
We're seeking a Research Scientist with deep expertise in Computer Vision to join our ML team. You'll be at the forefront of developing and deploying state-of-the-art vision models for medical imaging applications. This role focuses on training and scaling vision encoders for radiology diagnosis across multiple modalities including X-rays, CT scans, and MRI. You'll work with one of the largest and most diverse medical imaging datasets in the industry, pushing the boundaries of what's possible in AI-assisted diagnosis while maintaining the rigor required for clinical deployment.
Key Responsibilities
  • Design, train, and scale vision foundation models for radiology applications across X-ray, CT, and MRI modalities, implementing self-supervised / contrastive learning frameworks.
  • Evaluate model performance rigorously across academic benchmarks, internal offline datasets, and live production data.
  • Contribute hands-on to all stages of model development including dataset curation, architecture design, distributed training, and production deployment.
  • Stay current with cutting-edge research in computer vision and medical imaging AI.
  • Drive research and technical excellence through conference publications and technical blog posts, establishing best practices for training robust medical imaging models at scale.
Qualifications
  • 6+ years of academia/industry experience in computer vision/machine learning
  • Deep expertise in training vision encoder models at scale (e.g. ViT, ConvNeXt). Strong foundation in contrastive learning, self-supervised learning, and foundation model pretraining.
  • Track record of implementing complex models from research papers and adapting them to new domains
  • Proficiency in PyTorch or JAX, with experience training models on multi-GPU/distributed systems
  • Hands-on experience with medical imaging applications, particularly radiology (X-ray, CT, MRI)
  • Strong software engineering skills and ability to write production-quality code

Preferred Qualifications
  • Publications at top-tier conferences (CVPR, ICCV/ECCV, NeurIPS, ICLR, MICCAI)
  • Experience with 3D medical image processing and retrieval tasks
  • Knowledge of vision-language models and multimodal learning
  • Experience with model interpretability and explainability methods
  • Understanding of clinical evaluation metrics, clinical workflows, and healthcare data (DICOM, HL7, etc.)