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Robotics Perception Engineer Jobs in Portland, OR

Assembler I, Optics

Tualatin, OR

$16.75 - $20.50/hr

Operate robotic equipment and adhesive dispensers. Education/Experience & Skills: * High school ... perception, and the ability to focus on fine print. * Must wear required Personal Protective ...

Assembler I, Optics

Tualatin, OR · On-site

$16.75 - $20.50/hr

Operate robotic equipment and adhesive dispensers. Education/Experience & Skills: * High school ... perception, and the ability to focus on fine print. * Must wear required Personal Protective ...

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Robotics Perception Engineer information

See Portland, OR salary details

$30.8K

$112K

$179.2K

How much do robotics perception engineer jobs pay per year?

As of Jun 10, 2026, the average yearly pay for robotics perception engineer in Portland, OR is $111,995.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,600.00 and $134,700.00 per year, depending on experience, location, and employer.

What are Robotics Perception Engineers?

Robotics Perception Engineers are professionals who specialize in enabling robots to interpret and understand their environment using sensors and data processing algorithms. They work on developing and implementing computer vision, sensor fusion, and machine learning techniques so that robots can perceive objects, people, and surroundings. Their work is crucial for applications such as autonomous vehicles, drones, industrial automation, and service robots. By improving a robot's ability to 'see' and make sense of the world, they help create safer and more effective robotic systems.

What is the difference between Robotics Perception Engineer vs Computer Vision Engineer?

AspectRobotics Perception EngineerComputer Vision Engineer
Required CredentialsBachelor's or Master's in Robotics, Computer Science, or Electrical Engineering; experience with perception algorithmsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; strong programming skills in vision processing
Work EnvironmentRobotics labs, autonomous vehicle companies, industrial automationSoftware companies, tech startups, research labs focusing on image and video analysis
Industry UsageAutonomous vehicles, robotics, manufacturingHealthcare, security, consumer electronics, automotive

Robotics Perception Engineers focus on developing perception systems specifically for robots, integrating sensors and perception algorithms for navigation and interaction. Computer Vision Engineers primarily develop algorithms for interpreting visual data across various applications. While both roles require strong programming and understanding of perception, Robotics Perception Engineers specialize in sensor fusion and real-time processing within robotic systems, whereas Computer Vision Engineers work more broadly on image analysis and recognition tasks.

What are some common challenges faced by Robotics Perception Engineers when integrating new sensors into autonomous systems?

Robotics Perception Engineers often encounter challenges such as sensor calibration, data synchronization, and managing varying data quality when integrating new sensors. Ensuring that sensor data is accurately aligned in time and space is crucial for reliable perception in autonomous systems. Additionally, engineers must address the complexities of fusing data from multiple modalities (like cameras, LiDAR, or radar) while optimizing processing efficiency. Close collaboration with hardware and software teams is essential to troubleshoot integration issues and achieve robust, real-time perception.

What are the key skills and qualifications needed to thrive as a Robotics Perception Engineer, and why are they important?

To thrive as a Robotics Perception Engineer, you need strong expertise in computer vision, sensor fusion, machine learning, and proficiency in programming languages like C++ and Python, often supported by a degree in robotics, computer science, or a related field. Familiarity with tools and frameworks such as ROS (Robot Operating System), OpenCV, and deep learning libraries, as well as experience with sensors like LiDAR and cameras, is typically required. Excellent problem-solving abilities, teamwork, and adaptability help set standout professionals apart in this role. These competencies are crucial for enabling robots to accurately interpret and interact with their environment, leading to robust and reliable autonomous systems.
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