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Internship Perception Engineer Jobs (NOW HIRING)

Bot Auto

Intern, Deep Learning Engineer

Houston, TX

$14.25 - $19/hr

We are looking for MS/PhD interns to join our core AI team for a 3-6 month internship to tackle ... Implement and benchmark next-gen architectures (e.g., Multi-modal perception, Online Mapping ...

Bot Auto

Intern, Deep Learning Engineer

Houston, TX · On-site

$14.25 - $19/hr

We are looking for MS/PhD interns to join our core AI team for a 3-6 month internship to tackle ... Implement and benchmark next-gen architectures (e.g., Multi-modal perception, Online Mapping ...

Gradient Robotics

Software Engineer

San Francisco, CA · On-site

You'll work close to the hardware, from kernel and firmware up through the controls and perception ... with strong project or internship experience are welcome to apply) * Strong programming ...

Toyota Material Handling

Research Engineer

Greene, NY · On-site

$65K - $83K/yr

Explore emerging technologies in robotics, automation, perception systems, computer vision ... Internship, co-op, or professional experience in research and development (R&D). * Familiarity with ...

MVP Robotics

Robotics Software Engineer

Bradford, VT · On-site

... other perception sensors (e.g., LiDAR) * Path planning * Obstacle Detection/Collision Avoidance ... Minimum Bachelor's degree * 2+ Years experience in industry (internship/co-ops considered)

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How much do internship perception engineer jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for internship perception engineer in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 per hour, depending on experience, location, and employer.

What is an internship perception engineer?

An Internship Perception Engineer is a student or recent graduate who works on developing and improving perception systems, often within the fields of robotics, autonomous vehicles, or computer vision. Their responsibilities typically include processing sensor data (like cameras, LiDAR, or radar), developing algorithms for object detection and tracking, and contributing to machine learning models that help machines understand their environment. These internships offer hands-on experience with cutting-edge technologies and exposure to real-world engineering challenges. Interns usually work under the guidance of experienced engineers and may collaborate with teams across hardware, software, and research.

What types of projects does an internship perception engineer typically work on, and how do these contribute to the overall goals of the engineering team?

Internship Perception Engineers usually work on projects involving data collection, algorithm development, and sensor integration to help machines interpret their environments. These projects can include tasks like annotating sensor data, testing perception models (such as object detection or tracking), or supporting the deployment of perception systems in real-world scenarios. By contributing to these projects, interns help the team improve the accuracy and reliability of perception solutions, which are essential for applications like autonomous vehicles or robotics. Interns often collaborate closely with senior engineers and cross-functional teams, gaining hands-on experience and exposure to state-of-the-art technologies.

What are the key skills and qualifications needed to thrive as an internship perception engineer, and why are they important?

To thrive as an Internship Perception Engineer, you need a solid background in computer vision, machine learning, and programming languages such as Python or C++, often supported by coursework in robotics or artificial intelligence. Familiarity with tools like ROS, OpenCV, TensorFlow, and experience working with sensor data (e.g., LiDAR, cameras) are typically required. Strong problem-solving abilities, teamwork, and effective communication set top candidates apart in collaborative, research-driven environments. These skills are crucial for developing and integrating advanced perception algorithms that enable autonomous systems to interpret and interact with their surroundings.

What is the difference between Internship Perception Engineer vs Perception Engineer?

AspectInternship Perception EngineerPerception Engineer
Required CredentialsTypically pursuing or recently completed relevant degree (e.g., Computer Science, AI)Bachelor's or higher in related field, with experience preferred
Work EnvironmentInternship setting, learning-focused, entry-level tasksFull-time professional role, responsible for perception system development
Employer & Industry UsageInternship programs in tech companies, research labsEstablished companies in autonomous vehicles, robotics, AI
Search & Comparison IntentUnderstanding entry-level roles, internships, career pathProfessional expertise, career advancement, project responsibilities

In summary, an Internship Perception Engineer is an entry-level role designed for students or recent graduates gaining experience in perception systems, while a Perception Engineer is a full-time professional responsible for developing and maintaining perception algorithms in industry settings.

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Internship Perception Engineer jobs near you
Infographic showing various Internship Perception Engineer job openings in the United States as of August 2026, with employment types broken down into 67% Full Time, and 33% Temporary. Highlights an 100% In-person job distribution, with an average salary of $40,174 per year, or $19.3 per hour.

Intern, Deep Learning Engineer

Bot Auto

Houston, TX

$14.25 - $19/hr

Full-time, Internship

Re-posted 20 days ago

Job description

About Bot Auto 

Bot Auto is revolutionizing autonomous trucking by combining start-up agility with the wisdom of seasoned experts. We are looking for MS/PhD interns to join our core AI team for a 3-6 month internship to tackle real-world edge cases.

Key Responsibilities
  • SOTA Prototyping: Implement and benchmark next-gen architectures (e.g., Multi-modal perception, Online Mapping, Behavior Prediction, World Model).
  • Project Ownership: Own a targeted research project from data analysis to model verification under senior mentorship.
  • Scale Experimentation: Train, tune, and optimize deep learning models using our large-scale compute clusters and truck datasets.
Qualifications

Required:

  • Education: Current Master's or Ph.D. candidate in CS, Robotics, or a related field, specifically focusing on Deep Learning, Computer Vision, Robotics, or related fields. 
  • Technical Stack: Proficient in Python and PyTorch with clean coding practices.
  • Theoretical Core: Solid understanding of modern AI architectures, especially Transformers and its applications in different fields.
  • Commitment: Available full-time for at least 3 months.

Preferred:

  • Research Focus: Academic thesis or project experience in Multi-sensor Perception, Generative AI/Diffusion, Motion Prediction, or End-to-End Autonomous Driving.
  • Track Record: Publications or submissions at top conferences (e.g., CVPR, ICCV, NeurIPS, ICLR, ICRA).
  • Engineering Plus: Experience with Linux, Git, C++, or deployment tools like TensorRT/ONNX.

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