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Intern Computer Vision Deep Learning Engineer Jobs in Santa Clara, CA

Matroid

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

About Matroid Matroid is a full-service computer vision company that has developed an end-to-end ... We are looking for a world-class Deep Learning Software Engineer who is excited to operate at the ...

Matroid

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

About Matroid Matroid is a full-service computer vision company that has developed an end-to-end ... We are looking for a world-class Deep Learning Software Engineer who is excited to operate at the ...

Matroid

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

About Matroid Matroid is a full-service computer vision company that has developed an end-to-end ... We are looking for a world-class Deep Learning Software Engineer who is excited to operate at the ...

Imagry

Senior Deep Learning Engineer - Perception

San Jose, CA · On-site

$123K - $169K/yr

Senior Deep Learning Engineer, Computer Vision imagry.E4.E30@comeetapply.com Location: San Jose, CA , On Site We are looking for a capable and experienced Sr. Deep Learning Engineer to join our R&D ...

Imagry

Senior Deep Learning Engineer - Perception

San Jose, CA · On-site

$123K - $169K/yr

Description Senior Deep Learning Engineer, Computer Vision imagry.E4.E30@comeetapply.com Location: San Jose, CA , On Site We are looking for a capable and experienced Sr. Deep Learning Engineer to ...

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All JobsIntern Computer Vision Deep Learning Engineer JobsIntern Computer Vision Deep Learning Engineer Jobs in Santa Clara, CA

Intern Computer Vision Deep Learning Engineer information

See Santa Clara, CA salary details

$10

$20

$28

How much do intern computer vision deep learning engineer jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for intern computer vision deep learning engineer in Santa Clara, CA is $20.01, according to ZipRecruiter salary data. Most workers in this role earn between $16.92 and $22.60 per hour, depending on experience, location, and employer.

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

AspectIntern Computer Vision Deep Learning EngineerIntern Machine Learning Engineer
Required SkillsComputer vision, deep learning, CNNs, Python, TensorFlow/PyTorchMachine learning, algorithms, Python, scikit-learn, TensorFlow/PyTorch
Work EnvironmentResearch labs, tech companies, startups focusing on image/video analysisTech companies, research labs, startups working on diverse ML applications
Industry UsagePrimarily in computer vision projects like object detection, image segmentationBroader ML projects including predictive modeling, NLP, recommendation systems

Intern Computer Vision Deep Learning Engineers focus on image and video analysis using deep learning techniques, while Intern Machine Learning Engineers work on a wider range of ML applications. Both roles require strong Python skills and familiarity with deep learning frameworks, but their project focus and industry applications differ.

What types of projects or tasks can I expect to work on as an Intern Computer Vision Deep Learning Engineer?

As an Intern Computer Vision Deep Learning Engineer, you can expect to contribute to projects involving image or video analysis, such as object detection, image classification, or facial recognition. Your daily tasks might include data preprocessing, annotating datasets, training and evaluating deep learning models, and assisting with model optimization for deployment. You’ll often work closely with senior engineers and researchers, gaining hands-on experience with real-world datasets and cutting-edge frameworks. Collaboration with cross-functional teams, such as software developers and product managers, is common to ensure your models address practical business needs.

What does an Intern Computer Vision Deep Learning Engineer do?

An Intern Computer Vision Deep Learning Engineer assists in developing and improving algorithms that enable computers to interpret and understand visual information from the world, such as images and videos. They often work on tasks like image classification, object detection, and facial recognition using deep learning frameworks like TensorFlow or PyTorch. Interns typically help with data collection, model training, evaluation, and sometimes deployment, all under the guidance of experienced team members. This role is a great opportunity to gain hands-on experience in machine learning and computer vision while contributing to real-world projects.

What are the key skills and qualifications needed to thrive as an Intern Computer Vision Deep Learning Engineer, and why are they important?

To thrive as an Intern Computer Vision Deep Learning Engineer, you need a solid understanding of machine learning fundamentals, computer vision concepts, and proficiency in programming languages like Python, often supported by coursework or personal projects. Familiarity with deep learning frameworks such as TensorFlow or PyTorch and experience with image processing libraries like OpenCV are typically expected. Strong problem-solving abilities, curiosity, and effective teamwork skills help interns excel in fast-paced research and development environments. These skills are essential for contributing to innovative projects and adapting to the rapidly evolving field of computer vision.
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Intern Computer Vision Deep Learning Engineer jobs near you
Infographic showing various Intern Computer Vision Deep Learning Engineer job openings in Santa Clara, CA as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $41,617 per year, or $20 per hour.
Sr. Computer Vision Engineer (Deep Learning)

Sr. Computer Vision Engineer (Deep Learning)

Harbinger Motors Inc.

Mountain View, CA • On-site

$123K - $169K/yr

Other

Posted 14 days ago

Job description

We are seeking a highly skilled Senior Deep Learning Engineer to drive the development and deployment of advanced perception models for Advanced Driver Assistance Systems (ADAS). The successful candidate will play a key role in designing cutting-edge neural network architectures, optimizing model performance, and ensuring reliable deployment on embedded platforms. This position requires a balance of deep technical expertise, strong analytical thinking, and cross-functional collaboration. This role would sit in Mountain View, CA with PhantomAI, Harbinger's ADAS division. 


Responsibilities

  • Design and implement advanced deep learning architectures to enhance perception capabilities within ADAS systems.
  • Maintain and continuously improve existing models by optimizing performance, addressing issues, and refining architecture and algorithms.
  • Perform detailed root cause analysis of production issues and develop sustainable, high-quality solutions.
  • Optimize model performance with a focus on latency, efficiency, and resource utilization for real-time embedded deployment.
  • Integrate and validate deep learning algorithms on automotive-grade hardware and embedded SoCs.
  • Collaborate closely with data engineering, data annotation, and platform engineering teams to ensure smooth data flow and seamless model integration.
  • Provide regular updates and technical reports on model development, maintenance progress, and performance metrics to management.


Required Qualifications

  • 5+ years of professional experience developing, training, validating, and deploying deep learning-based perception models for ADAS or related computer vision applications.
  • In-depth understanding of training and inference pipelines, including data loading, augmentation, and loss function design.
  • Advanced degree (M.S. or Ph.D.) in Computer Vision, Robotics, Machine Learning, or a closely related discipline, or equivalent industry experience.
  • Strong proficiency in Python and a deep understanding of software design principles and development best practices.
  • Expertise in PyTorch (preferred) or TensorFlow for large-scale model development and experimentation.
  • Practical experience with data pipelines, distributed training, and machine learning experiment management tools.
  • Proven ability to work effectively in a collaborative, cross-functional team environment.


Preferred Qualifications

  • Comprehensive understanding of machine learning algorithms, including classification, regression, and clustering methods.
  • Experience deploying and optimizing models for embedded or automotive SoCs (e.g., NVIDIA Drive, TI TDA4, Qualcomm Snapdragon).
  • Proficiency in model optimization techniques such as quantization, pruning, and knowledge distillation.
  • Doctorate (Ph.D.) in Computer Science, Artificial Intelligence, or related field is a plus.
  • Strong programming experience in Python and/or C++ within Linux development environments.
  • Familiarity with automotive perception workflows, datasets, and evaluation frameworks (e.g., KITTI, Waymo, Euro NCAP)

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