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Intern Computer Vision Deep Learning Engineer Jobs in Concord, CA

... vision-based localization * Collaborate with deep learning, device, and cloud teams to improve ... Master of Science degree or the foreign equivalent in Electrical and Computer Engineering, Robotics ...

Experience in machine learning algorithms for vision problems, including deep learning ... S. or Ph.D. and 5+ years of work in computer vision, software or related field * Strong ...

... and deep learning; identify and apply relevant advancements to Tesla's challenges Qualifications : Required : • Degree in Computer Science, Computer Engineering, Electrical Engineering, Data ...

Machine Learning Engineer - San Francisco, CA What if you could apply quant-style trading ... Strong judgment on deep learning vs classical ML approaches * Ability to implement research with a ...

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Our work is at the cutting edge of computer vision and deep learning, which also includes working ... Solve idiosyncratic statistical, geometric, and engineering problems * Work closely with a full ...

We are looking for developers who are excited about staying at the forefront of deep learning ... You are very knowledgeable in at least one focus area of machine learning, such as computer vision ...

Machine Learning Engineer - San Francisco, CA What if you could apply quant-style trading ... Strong judgment on deep learning vs classical ML approaches * Ability to implement research with a ...

Machine Learning Engineer - San Francisco, CA What if you could apply quant-style trading ... Strong judgment on deep learning vs classical ML approaches * Ability to implement research with a ...

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Intern Computer Vision Deep Learning Engineer information

See Concord, CA salary details

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

As of Jun 14, 2026, the average hourly pay for intern computer vision deep learning engineer in Concord, CA is $18.69, according to ZipRecruiter salary data. Most workers in this role earn between $15.82 and $21.11 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.
What are popular job titles related to Intern Computer Vision Deep Learning Engineer jobs in Concord, CA? For Intern Computer Vision Deep Learning Engineer jobs in Concord, CA, the most frequently searched job titles are:
What cities near Concord, CA are hiring for Intern Computer Vision Deep Learning Engineer jobs? Cities near Concord, CA with the most Intern Computer Vision Deep Learning Engineer job openings:
Senior State Estimation Engineer

Senior State Estimation Engineer

Hayden AI

San Francisco, CA • On-site

$200K - $260K/yr

Full-time

Posted 23 days ago


Job description

About Us
At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.
From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.
What the job involves
As a Senior State Estimation Engineer at Hayden AI, you will be asked to derive and implement novel real-time pose estimation algorithms. Research, develop and implement algorithms to solve large-scale mapping. Collaborate with other engineers to develop algorithms for in-situ and in-factory multi-sensor calibration.
Responsibilities
  • Contribute to high impact, multidisciplinary projects across teams
  • Program and develop software in C++ and/or python
  • Derive and implement novel, real-time pose estimation algorithms
  • Research, develop and implement algorithms to solve problems such as large-scale mapping, probabilistic object tracking, online/offline sensor calibration and/or vision-based localization
  • Collaborate with deep learning, device, and cloud teams to improve overall system architectures
  • Provide mentorship to our junior engineers

Required Qualifications
  • Master of Science degree or the foreign equivalent in Electrical and Computer Engineering, Robotics, Machine Learning, Computer Science, Electrical Engineering or a related field.
  • Five (5)+ years of experience in the position offered, as a software engineer, software engineer intern, or a related state estimation engineer role.
  • Five (5) years of experience with all of the following: programming in C++; designing and developing software; classical ML, Linear Algebra,
    Stochastic Processes, Geometric Computer Vision and Optimization (Convex, Nonlinear); Kalman Filter, MAP, Sequential Monte Carlo (particle
    filter), Nonlinear Least squares, IRLS and MHT; GPS, IMU, camera and wheel odometry.
  • Experience deploying SLAM/VIO estimators in a real-world application.
  • Work with multiple sensors such as GPS, IMU, camera, LIDAR, and wheel odometry.