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Internship Computer Vision Robotics Jobs (NOW HIRING)

Molg

Computer Vision Engineer

Sterling, VA · On-site

$110K - $130K/yr

Using robotics, computational design, and AI, our systems turn today's e-waste into resilient, data ... As a Computer Vision Engineer, you will: * Drive the architecture, development, and deployment of ...

MOLG Inc.

Computer Vision Engineer

Sterling, VA

$110K - $130K/yr

Molg builds robotics microfactories and software to autonomously assemble and disassemble complex ... As a Computer Vision Engineer, you will be responsible for: * Continuous design, development ...

Brachium

Robotics Vision Engineer

San Ramon, CA · On-site

Develop and evaluate state-of-the-art computer vision algorithms for real-time control of robots and other hardware devices * Port, implement, and optimize analytics and machine learning algorithms ...

Brachium

Robotics Vision Engineer

San Ramon, CA · On-site

Develop and evaluate state-of-the-art computer vision algorithms for real-time control of robots and other hardware devices * Port, implement, and optimize analytics and machine learning algorithms ...

Brachium

Robotics Vision Engineer

San Ramon, CA · On-site

Develop and evaluate state-of-the-art computer vision algorithms for real-time control of robots and other hardware devices * Port, implement, and optimize analytics and machine learning algorithms ...

Actalent

Software Engineer

Pittsburgh, PA

Software Engineer - R&D (Machine Learning, Computer Vision, Automated Driving) This role focuses on research and advanced development in machine learning, computer vision, robotics, and automated ...

Qualcomm

Computer Vision Engineer

San Diego, CA · On-site

$118K - $139K/yr

... robotics, and immersive AR/VR platforms. The group's work spans computer vision and video algorithm development, mapping these algorithms to computer vision and neural-processing accelerator ...

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Internship Computer Vision Robotics information

What are the key skills and qualifications needed to thrive as an Internship Computer Vision Robotics, and why are they important?

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 are Internship Computer Vision Robotics positions?

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 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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Internship Computer Vision Robotics jobs near you
Infographic showing various Internship Computer Vision Robotics job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 98% Full Time, and 1% Part Time. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution.

Computer Vision Engineer - Autonomy & Perception

Pivotal

Palo Alto, CA

$131K - $154K/yr

Full-time

Posted 11 days ago

Job description

Pivotal is the leader in the emerging market of electric Vertical Takeoff and Landing (eVTOL) aircraft. We design, develop, and manufacture light eVTOL aircraft and are renowned for the BlackFly aircraft the world's first light eVTOL to fly manned missions and enter the consumer market. 
 
Efficient, compact, and simple, Pivotal aircraft are designed for a wide range of consumer, public service, and defense applications. Our distinctive tilt-aircraft architecture and scalable platform have been flying for over 10 years. Last year we announced our next-generation aircraft, the Helix, which is rapidly progressing toward general release and scalable production in 2026. 
 
Mobility is one of the most highly-valued areas of modern technology investments. This is the right company, in the right space, the right strategy, at the right time. If you are ready for adventure, we invite you to join our amazing team and grow with us.

The Autonomy team at Pivotal develops advanced autonomy capabilities for our aircraft, enabling safe, precise, and reliable mission execution from takeoff to landing. We are seeking a Computer Vision Engineer to support the development of next-generation perception systems for our autonomous aerial platforms, including the Helix family of systems. 

In this role, you will collaborate with autonomy, guidance, navigation and control (GNC), flight software, and AI engineers to design, implement, and deploy computer vision algorithms that operate effectively in dynamic, real-world environments. You will work across object detection, tracking, visual localization, scene understanding, sensor fusion, and perception-driven autonomy to enable robust autonomous operations in challenging mission scenarios. 

The ideal candidate combines strong computer vision fundamentals with practical experience deploying perception systems on robotic or autonomous platforms. You will play a key role in developing vision capabilities that support navigation, obstacle avoidance, target tracking, and mission autonomy while contributing to the broader autonomy stack deployed on operational aircraft. 

Responsibilities

  • Perception & Computer Vision: Design and develop perception systems for autonomous aerial platforms operating in GPS-denied and contested environments; implement object detection, classification, segmentation, and tracking algorithms using RGB, thermal, and multimodal sensor data; develop visual perception pipelines for obstacle detection, collision avoidance, and situational awareness; build scene understanding capabilities to support autonomous navigation and mission execution; evaluate and integrate state-of-the-art computer vision and AI techniques into operational systems. 

  • Visual Navigation & Localization: Develop visual-inertial odometry, localization, and mapping algorithms; implement vision-based navigation solutions for degraded and GPS-denied environments; support SLAM and feature-based localization systems; design robust estimation methods that fuse camera, IMU, GPS, lidar, and radar data; improve navigation performance through sensor fusion and environmental awareness. 

  • Machine Learning & AI: Develop, train, and deploy deep learning models for onboard perception; create data processing, labeling, augmentation, and evaluation pipelines; optimize neural networks for real-time inference on embedded computing platforms; analyze model performance and improve robustness across operational conditions; support deployment of perception models on edge AI hardware. 

  • Camera Systems & Sensor Integration: Integrate and evaluate diverse imaging systems including RGB, stereo, fisheye, thermal, and event-based cameras; develop camera calibration workflows and sensor characterization procedures; support multi-camera synchronization and calibration efforts; improve image quality, calibration accuracy, and perception system reliability; collaborate with hardware teams to evaluate and integrate emerging sensor technologies. 

  • Testing & Validation: Develop simulation and testing frameworks for perception algorithms; support software-in-the-loop, hardware-in-the-loop, and flight testing activities; analyze flight data to identify performance gaps and improve perception robustness; establish metrics and validation procedures for autonomous perception systems; document system performance and support field deployments. 

Qualifications

  • Education: Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Aerospace Engineering, or a related technical field. 

  • Experience: 2–4 years of industry experience in computer vision, robotics, machine learning, or autonomous systems OR Master's degree with 1–2 years of industry experience. 

  • Strong proficiency in C++, Python, or Rust. 

  • Experience with OpenCV and modern computer vision frameworks. 

  • Experience developing perception systems using PyTorch, TensorFlow, or similar machine learning frameworks. 

  • Strong understanding of image processing, geometric vision, and camera systems. 

  • Experience with object detection, tracking, segmentation, and machine learning-based perception algorithms. 

  • Familiarity with sensor fusion and state estimation techniques. 

  • Experience with ROS/ROS2 or similar robotics middleware. 

  • Experience developing software in Linux environments. 

Preferred Qualifications
  • Master's or PhD in Computer Vision, Robotics, Machine Learning, Computer Science, or a related field. 
  • Experience with autonomous aircraft, UAVs, robotics, or aerospace systems. 
  • Experience with visual SLAM, visual-inertial odometry, or localization systems. 
  • Knowledge of camera calibration, multi-camera systems, and geometric computer vision. 
  • Experience integrating lidar, radar, thermal cameras, and inertial sensors into perception systems. 
  • Experience deploying AI models on embedded platforms such as NVIDIA Jetson or similar edge computing hardware. 
  • Familiarity with simulation environments such as Gazebo, Isaac Sim, AirSim, or equivalent. 
  • Experience optimizing perception systems for real-time performance and resource-constrained platforms. 
  • Contributions to open-source robotics, autonomy, or computer vision projects. 
  • Familiarity with defense industry standards and security clearance processes. 
Attributes aligned with Core Values
  • Demonstrates a proactive safety mindset by embedding safety into daily operations, identifying and mitigating risks through assessments and training, encouraging open dialogue on safety concerns, and continuously improving protocols to ensure a safe work environment.
  • Puts customers at the center of every action by deeply understanding their challenges, delivering exceptional value, and striving to exceed expectations to support their success as our core purpose.
  • Actively seeks and values diverse stakeholder perspectives, builds cross-functional relationships, and fosters trust through empathetic, fact-based communication—committing to shared decisions for the greater good.
  • Drives results with clarity and purpose by focusing on what matters most, adapting to change, taking initiative, and owning outcomes while aligning actions with a clear understanding of success at every level.
  • Navigates ambiguity with resilience and bold thinking, challenges the status quo, and combines innovative ideas with practical best practices to overcome obstacles and drive progress.
  • Fosters a high-performance culture grounded in respect, professionalism, and support—balancing high expectations with a healthy, collaborative environment and being a trusted, dependable teammate.
Applicants must be eligible for employment in the United States and willing to work onsite at our HQ office in Palo Alto, CA.
 
Pivotal offers a comprehensive benefits package, including medical, dental, vision, and 401k plans.
 
Pivotal is an Equal Opportunity Employer. Pivotal does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.

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.