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Intern Computer Vision Deep Learning Engineer Jobs in San Diego, CA

Qualcomm

Computer Vision System Engineer

San Diego, CA · On-site

Engineering Group, Engineering Group > Video Systems, HW Architecture General Summary: Qualcomm ... The team develops next-generation mobile computer vision and deep learning solutions for imaging ...

Qualcomm

Computer Vision System Engineer

San Diego, CA · On-site

$150 - $200/hr

Engineering Group, Engineering Group > Video Systems, HW Architecture General Summary: Qualcomm ... The team develops next-generation mobile computer vision and deep learning solutions for imaging ...

Cesna Group

Junior Computer Vision Engineer

San Diego, CA · On-site

$100K - $200K/yr

... and deep learning * - To design, implement, and deploy full-stack computer vision and machine ... Master's degree in Computer Science or Electrical Engineering plus 2 or more years of relevant ...

Qualcomm

Computer Vision Engineer

San Diego, CA · On-site

$118K - $139K/yr

Leverage advanced video and computer vision engineering expertise to research, design, and ... Hands-on experience with modern deep learning architectures. * Strong coding skills in Python and C ...

Nutanix

Computer Vision Engineer

San Diego, CA · On-site

$150 - $200/hr

Principal Duties and ResponsibilitiesLeverage advanced video and computer vision engineering ... Hands ‑ on experience with modern deep learning architectures.Strong coding skills in Python and ...

TEEMA

Computer Vision Engineer

San Diego, CA · On-site

$125K - $130K/yr

... Computer Engineering, Electrical Engineering, or related field * 3+ years of computer vision ... deep learning) * Experience with real-time optimization, parallel processing, or embedded CV ...

Qualcomm

Computer Vision Engineer

San Diego, CA · On-site

$150 - $200/hr

Leverage advanced video and computer vision engineering expertise to research, design, and ... Hands‑on experience with modern deep learning architectures. * Strong coding skills in Python and ...

Cesna Group

Computer Vision R&D Engineer

San Diego, CA · On-site

$100K - $200K/yr

We are seeking an Intermediate Computer Vision R&D Engineer to join our team. The candidate will be ... CNN/deep learning, shallow learning and their optimizations for efficient implementation on ...

Apple Inc.

Video Machine Learning Engineer

San Diego, CA · On-site

$150 - $200/hr

Proficiency in one or more deep learning frameworks such as PyTorch or TensorFlow. * Experience with computer vision and/or image and video processing techniques. * Strong programming skills in ...

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Intern Computer Vision Deep Learning Engineer information

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

As of Sep 9, 2026, the average hourly pay for intern computer vision deep learning engineer in San Diego, CA is $18.09, according to ZipRecruiter salary data. Most workers in this role earn between $15.34 and $20.43 per hour, depending on experience, location, and employer.

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?

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.

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 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 are the most commonly searched types of Computer Vision Deep Learning Engineer jobs in San Diego, CA?

The most popular types of Computer Vision Deep Learning Engineer jobs in San Diego, CA are:

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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 San Diego, CA as of September 2026, with employment types broken down into 1% As Needed, 71% Full Time, 20% Part Time, 7% Contract, and 1% Nights. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $37,622 per year, or $18.1 per hour.

Senior Machine Learning Engineer, Computer Vision/VLM

San Diego, CA

Waymo
Internet and IT • 1 - 5K employees
Learn more about Waymoexternal

$110K - $152K/yr

Full-time

Re-posted 24 days ago

Key responsibilities

  • Develop and train computer vision and multimodal models to extract semantic information from driving logs.

  • Design and implement a scalable AI agent framework that integrates foundation models with perception outputs and knowledge bases.

  • Own the full system lifecycle, from model development and prototyping to production deployment and scaling.

Job description

In Semantics, our team's mission is to create the highest-fidelity, most comprehensive offboard perception autolabels at a massive scale, serving as the foundation for training and validating the AV stack. We are an advanced ML and engineering team that leverages state-of-the-art computer vision, deep learning, and generative AI to automatically analyze driving logs, generate rich scene understanding, and power the data engine that enables Waymo to scale safely and efficiently.

In this hybrid role, you will report to a Senior Staff Technical Lead Manager.

You will:

  • Develop and train state-of-the-art computer vision / multimodal models (e.g., Gemini) to extract the rich semantic information (e.g., object attributes, scene properties, interaction dynamics) required by the AI agent.
  • Design and implement a scalable AI agent framework that integrates large foundation models (e.g., Gemini) with the outputs of our perception models and internal knowledge bases.
  • Develop and apply Fine-tuning and Reinforcement Learning (RL) techniques to create a "data flywheel," continuously improving the system's captioning and reasoning abilities through automated feedback.
  • Develop and prototype novel prompting strategies for Vision-Language Models (VLMs) to elicit complex, causal reasoning about driving scenarios.
  • Collaborate closely with the ML Infra, Perception, Behavior, and AI Foundation teams to define data requirements and integrate the captioning system into the broader ML development lifecycle.
  • Own the full system lifecycle, from advanced model development and prototyping to production deployment and scaling for massive data generation

You have:

  • Master's degree in Computer Science, or a related technical field.
  • 4+ years of hands-on experience training and shipping deep learning models for computer vision tasks (e.g., detection, segmentation, video understanding) using Python and frameworks like PyTorch, JAX, or TensorFlow.
  • 1+ years of demonstrated experience working with large language models (LLMs) or vision-language models (VLMs) in areas such as fine-tuning, prompting, or Retrieval-Augmented Generation (RAG).
  • Strong software engineering fundamentals, including designing scalable and reliable systems.
  • Experience building and managing large-scale data processing pipelines for ML training.
  • Proven ability to work autonomously and lead complex technical projects in a fast-paced R&D environment.

We prefer:

  • PhD in Computer Science, or a related technical field.
  • Publication record in top-tier AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR).
  • Hands-on experience with Reinforcement Learning, especially RLHF, RLAIF, or applying RL to language/agentic tasks.
  • Experience with modern techniques in self-supervised, weakly-supervised, or multi-task learning for perception.
  • Experience building with AI agent frameworks (e.g., LangChain, LlamaIndex) or developing autonomous agentic systems.
  • Familiarity with the challenges of multimodal perception in robotics or autonomous driving.
  • A track record of impactful cross-functional collaboration.

Apply