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Internship Computer Vision Robotics Jobs in California

Skild AI

Computer Vision AI & ML Engineer

San Mateo, CA · On-site

$127K - $149K/yr

Company Overview At Skild AI, we are building the world's first general purpose robotic ... Position Overview We are seeking a Computer Vision AI & ML Engineer to design, build, and deploy ...

Goodfire

Account Executive, Robotics

San Francisco, CA · On-site

Ability to learn robotics, embodied AI, computer vision, reinforcement learning, autonomy, and deployment concepts quickly and communicate credibly with engineers, researchers, CTOs, and Heads of AI.

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Internship Computer Vision Robotics information

What is an internship computer vision robotics?

Internship Computer Vision Robotics positions are temporary roles designed for students or early-career professionals to gain practical experience in applying computer vision techniques within robotic systems. Interns in these roles typically work on projects involving image processing, object detection, 3D vision, and integrating visual data into robotic control systems. These internships help candidates build technical skills, gain exposure to real-world robotics challenges, and often require knowledge of programming languages such as Python or C++, as well as familiarity with machine learning frameworks. They are commonly offered by research labs, tech companies, and robotics startups.

What are the key skills and qualifications needed to thrive as an internship computer vision robotics?

To thrive in an Internship Computer Vision Robotics role, you typically need a solid background in computer science, mathematics, and robotics, often supported by coursework or projects in machine learning and image processing. Familiarity with programming languages like Python or C++, and experience using tools such as OpenCV, ROS, and deep learning frameworks (e.g., TensorFlow or PyTorch) are commonly required. Strong problem-solving, teamwork, and effective communication skills set candidates apart in multidisciplinary environments. These skills are essential for developing innovative solutions and collaborating on complex robotics projects.

What types of projects and technologies will I typically work on during an internship in computer vision robotics?

As an intern in computer vision robotics, you will often work on hands-on projects involving tasks like object detection, image segmentation, sensor data processing, or robotic navigation. You may use programming languages like Python or C++, and frameworks such as OpenCV, ROS (Robot Operating System), and TensorFlow or PyTorch for machine learning components. Interns collaborate closely with engineers and researchers, participating in code reviews, testing algorithms on real or simulated robots, and troubleshooting system integration. This role offers exposure to both software development and hardware interaction, providing a comprehensive experience in robotics and computer vision.

What is the difference between Internship Computer Vision Robotics vs Internship Machine Learning?

AspectInternship Computer Vision RoboticsInternship Machine Learning
Required CredentialsRelevant coursework, basic programming skills, familiarity with robotics and vision toolsProgramming skills, math background, familiarity with algorithms and data analysis
Work EnvironmentRobotics labs, hardware integration, software developmentData analysis, software development, research environments
Employer & Industry UsageRobotics companies, research labs, tech firms working on autonomous systemsTech companies, research institutions, AI startups

Internship Computer Vision Robotics focuses on developing systems that enable robots to interpret visual data, combining hardware and software skills. In contrast, Internship Machine Learning emphasizes designing algorithms to analyze data and build predictive models. Both roles require programming knowledge but differ in their application areas and work environments.

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Cities in California with the most Internship Computer Vision Robotics job openings:

Internship Computer Vision Robotics jobs near you

Senior Computer Vision / Applied AI Engineer

Simbe Robotics

San Francisco, CA • On-site

$160K - $200K/yr

Full-time

Posted 17 days ago

Job description

Simbe is building the AI powered operating system for physical retail. Our autonomous robots and multimodal computer vision platform turn complex, constantly changing stores into accurate, actionable intelligence for leading retailers around the world. Simbe combines robotics, computer vision, machine learning, data infrastructure, and customer focused product design to help retailers improve shelf availability, price and promo execution, inventory accuracy, and store team productivity.

Simbe is looking for a Senior Computer Vision / Applied AI Engineer to build production AI systems that turn store imagery into trusted retail intelligence. This role will work across dense product detection, price tag and promo tag detection, OCR, barcode decoding, product association, segmentation, visual search, model evaluation, and customer specific model improvements. The right person isa strong ML engineer, an exceptional software engineer, and a practical builder who enjoys messy real world data, rapid iteration, and measurable customer impact.

Why This Role Is High Impact
  • You will work on dense, cluttered, real world visual scenes where accuracy directly drives customer value.
  • You will help improve core Simbe use cases such as out of stock detection, price accuracy, promo compliance, top stock, and product location intelligence.
  • You will work on the full model lifecycle: data, annotation quality, training, evaluation, release, monitoring, and production debugging.
Responsibilities
  • Build production CV models. Design, train, validate, and deploy models for object detection, segmentation, OCR, barcode localization, product recognition, shelf understanding, and other customer facing computer vision tasks.
  • Own dataset quality. Curate, clean, version, and analyze large real world training datasets, including hard negative mining, annotation QA, data audits, and active learning workflows.
  • Improve model performance. Research and implement model architecture, loss function, data augmentation, synthetic data, and evaluation improvements that increase precision, recall, latency, and robustness across customers.
  • Support model releases. Contribute to model validation, release gates, inference wrappers, ONNX/TensorRT exports, and production monitoring so models are reliable in customer environments.
  • Develop tooling. Build internal tools for model evaluation, annotation review, error mining, data visualization, dataset exports, and deployment readiness.
  • Partner cross functionally. Work closely with Product, Customer Success, Data, Robotics Software, and Field Operations to turn customer issues into model and pipeline improvements.
  • Stay current. Track modern work in open vocabulary detection, promptable segmentation, multimodal product understanding, visual search, OCR, and edge inference, and evaluate where it can create value for Simbe.
Required Qualifications
  • 5+ years of experience in computer vision, applied machine learning, robotics perception, or related production AI systems.
  • Strong Python experience and hands on experience with PyTorch or TensorFlow.
  • Demonstrated experience using AI-assisted coding and automation tools to accelerate software development, debugging, experimentation, and engineering workflows, with strong judgment around validating and reviewing AI-generated output.
  • Experience training and evaluating object detection, segmentation, OCR, visual search, or image recognition models.
    Strong understanding of dataset curation, annotation quality, model evaluation, error analysis, and experimentation.
  • Experience building maintainable production code and data pipelines in a Linux based environment.
  • Ability to balance research quality with production constraints such as latency, compute, memory, robustness, and ease of deployment.
  • Strong communication skills and a customer value mindset.
Bonus Qualifications
  • Experience with retail, product recognition, shelf intelligence, OCR, barcode decoding, fine grained recognition, or visual product search.
  • Experience with ONNX, TensorRT, CUDA, quantization, model profiling, or edge deployment.
  • Experience with C++, ROS/ROS2, RGBD cameras, 3D geometry, homography, calibration, or robotic perception.
  • Experience with FiftyOne, CVAT, Labelbox, Roboflow, or other data centric ML tools.
  • Experience with synthetic data generation, simulation, active learning, or automated annotation workflows.
  • Publications, patents, open source contributions, or production systems in relevant CV/AI domains.
$160,000 - $200,000 a year

The base salary offered is based on market location and may vary depending on individualized factors for job candidates, including job related knowledge, skills, experience, and other objective business considerations. Subject to those same considerations, the total compensation package for this position may also include equity compensation, in addition to a full range of medical, financial, and other benefits. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

Simbe Values: R. E. T. A. I. L.

  • Result Driven - We are customer centric and results driven. We strive to create immense value for our team, partners, customers, and investors.

  • Empathetic - We are sensitive and mindful. We support each other in challenging times, both professionally and personally.

  • Transparent - We value open communication internally, and with our partners and customers. We are receptive to feedback.

  • Agile - We are eager to learn and adapt quickly to changes and customer needs.

  • Innovative - We are bold and innovative, with an intense focus on product design, user experience, and customer value.

  • Leaders - We strive for excellence. We are accountable, the best at what we do, and leaders in our field.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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