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Intern Computer Vision Deep Learning Engineer Jobs in Concord, CA

Required : • 3 to 5 years of industry experience in full-stack Deep Learning and Computer Vision ... data engineering, model tuning, and model serving • Technical expertise demonstrated through ...

Develop and deploy deep learning models, including vision language models (VLMs) and Large Language ... Currently pursuing a Masters or PhD program in Computer Science, Machine Learning, Robotics, or ...

Develop and deploy deep learning models, including vision language models (VLMs) and Large Language ... Currently pursuing a Masters or PhD program in Computer Science, Machine Learning, Robotics, or ...

Develop and deploy deep learning models, including vision language models (VLMs) and Large Language ... Currently pursuing a Masters or PhD program in Computer Science, Machine Learning, Robotics, or ...

Our team tackles complex data science and ML engineering challenges related to product ... Machine Learning, NLP, Computer Vision, Deep-learning, Python, GenAI Additional Qualifications:

Our team tackles complex data science and ML engineering challenges related to product ... Machine Learning, NLP, Computer Vision, Deep-learning, Python, GenAI Additional Qualifications:

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Deep Learning: Experience with neural networks, transformers, and CNNs. * NLP/LLMs: RAG systems, prompt engineering, vector databases, fine-tuning, and modern orchestration tools. * Computer Vision:

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 ...

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 ...

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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:
Staff Software Engineer, Deep Learning Acceleration

Staff Software Engineer, Deep Learning Acceleration

Aurora Innovation

San Francisco, CA • On-site

$189K - $274K/yr

Full-time

Posted 13 days ago


Job description

Who we are
Aurora's mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.
The Aurora Driver will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone.
At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit aurora.tech or follow us on LinkedIn.
Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. As a Staff Software Engineer focusing on Deep Learning Acceleration at Aurora, you will play a pivotal role in enhancing the performance of Deep Learning networks utilized in our Autonomous Vehicle (AV) systems.
Your primary responsibility will be to conduct thorough performance analysis and optimization of these networks, ensuring they operate efficiently both onboard the vehicle and during training on large-scale data centers. This position requires a deep understanding of software architecture, system performance, and latency issues, as you will be tackling various challenges that arise in these areas. You will collaborate with a team of talented engineers and researchers to develop solutions that improve the overall efficiency and reliability of our self-driving technology. Your work will directly contribute to making transportation safer and more accessible. The role demands a strong analytical mindset, particularly in performance troubleshooting, where you will utilize techniques such as profiling and the roofline model to identify bottlenecks and optimize performance. In addition to your technical skills, you will need to be adaptable and quick to learn new technologies, as the field of deep learning and autonomous systems is rapidly evolving. Strong communication skills are essential, as you will be working in a fast-paced environment with large code bases and collaborating with cross-functional teams.
In this role you will
  • Conduct performance analysis and optimization of Deep Learning networks running on the Autonomous Vehicle (AV).
  • Optimize software architecture, system performance, and latency for deep learning applications.
  • Work on deployment of deep learning models on the AV and training on large-scale data centers.
  • Troubleshoot performance issues using profiling and roofline model techniques.
  • Collaborate with cross-functional teams to enhance the efficiency of self-driving technology.

Required Qualifications
  • Minimum 5+ years of professional experience in software engineering.
  • BS, MS, or PhD in Computer Science or a related field.
  • Strong programming skills in CUDA, C++ and Python
  • Extensive experience in high-performance computing and parallel programming, specializing in optimizing workloads to reduce GPU memory usage, minimize latency, and/or maximize throughput.
  • Proficiency in leveraging performance analysis tools such as NVIDIA Nsight Systems , Nsight Compute and applying techniques like roofline model for performance optimization.
  • Hands-on experience in optimizing DL/ML workloads at the framework level using at least one deep learning framework (e.g., PyTorch, TensorFlow), ensuring efficient and scalable model deployment.
  • Strong understanding of the fundamentals of computer vision and transformer-based deep learning architectures, with proficiency in foundational neural network building blocks.
  • Strong analytical skills for diagnosing and troubleshooting performance bottlenecks in complex systems.
  • Demonstrated ability to quickly learn and adapt to emerging technologies and tools in a fast-paced environment
  • Experience working on large code bases in a fast-growing environment.
  • Strong communication skills, enabling effective teamwork across multidisciplinary teams.
  • Comfortable working in Linux/Unix environments.

Desirable Qualifications
  • Hands-on experience in motion planning or related fields such as robotics, autonomous systems, systems software, or computer vision.
  • Experience with TensorRT, OpenAI Triton, Mojo and other inference acceleration tools.

The base salary range for this position is $189,000 - $274,000. Aurora's pay ranges are determined by role, level, and location. Within the range, the successful candidate's starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.
#LI-Mid-Senior
Working at AuroraAt Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together - all without any jerks.
We believe in-person work increases collaboration, empathy and our ability to lead effectively. As a result, we operate in a hybrid work environment where Aurorans are in office at least 3 days per week.
Our Careers page provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom.
Our commitment to safety
At the core of everything we do is our commitment to safety. Building best-in-class self-driving technology will take time, and we believe that each employee at Aurora has a role in contributing to safety, every step of the way. Aurora expects commitment to our safety policies from every employee, and seeks candidates who take an active responsibility, can contribute to building an atmosphere of trust, and invest in the organization's long-term success by prioritizing working safely, no matter what.
Our commitment to inclusion
Aurora considers candidates without regard to their race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, pregnancy status, parent or caregiver status, ancestry, political affiliation, veteran and/or military status, physical or mental disability, or any other status protected by federal or state law. Aurora considers qualified applicants with criminal histories, consistent with applicable federal, state, and local law. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at careersiteaccommodations@aurora.tech.
For California applicants, information collected and processed as part of your application and any job applications you choose to submit is subject to Aurora's California Employment Privacy Policy.