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Robotics Perception Engineer Jobs in Novato, CA (NOW HIRING)

Perception Engineer

San Francisco, CA ยท On-site

$130K - $170K/yr

This role bridges data science, software engineering, and robotics to deliver reliable, highโ€‘throughput perception performance on edge hardware. What You'll Own: * Design, train, validate and fine ...

Senior Perception Engineer

San Francisco, CA ยท On-site

$170K - $240K/yr

Chef Robotics is accelerating the deployment of intelligent machines in the physical world ... As a Perception Engineer, you will own the full stack of how our robots see and understand the ...

Senior Perception Engineer

San Francisco, CA ยท On-site

$170K - $240K/yr

Chef Robotics is accelerating the deployment of intelligent machines in the physical world ... As a Perception Engineer, you will own the full stack of how our robots see and understand the ...

Perception Engineer

San Francisco, CA ยท On-site

$130K - $175K/yr

Educational Background: BS/MS in Robotics, Computer Science, Electrical Engineering, or a relevant technical degree * Experience: 3+ years of experience in perception or signal processing * Technical ...

Educational Background: BS/MS in Robotics, Computer Science, Electrical Engineering, or a relevant technical degree * Experience: 3+ years of experience in perception or signal processing * Technical ...

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Robotics Perception Engineer information

See Novato, CA salary details

$34K

$124K

$198.4K

How much do robotics perception engineer jobs pay per year?

As of Jun 10, 2026, the average yearly pay for robotics perception engineer in Novato, CA is $123,987.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $149,100.00 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.
What cities near Novato, CA are hiring for Robotics Perception Engineer jobs? Cities near Novato, CA with the most Robotics Perception Engineer job openings:

Machine Learning Engineer - Robot Perception

Maven Robotics

San Francisco, CA โ€ข On-site

Full-time

Posted 9 days ago


Job description

Company Overview
Maven Robotics is building the world's leading general-purpose AI robots.
We are currently operating in stealth and are growing the world's best team in AI robotics. We are looking for self-starters that are the world's best in their field, who can innovate from a deep understanding of the fundamentals, and who share our values of unwavering truth seeking and integrity, humility, curiosity, and relentless determination.
Role Description
We are looking to recruit an exceptional Machine Learning Engineer - Robot Perception to design, implement, test, and deploy robot perception algorithms that power our robots' ability to understand and interact with the world.
In this role you will:
  • Develop, train, and deploy ML-based perception algorithms for object detection, pose estimation, tracking, and scene understanding.
  • Integrate sensor fusion techniques using cameras, depth sensors, IMUs, and tactile feedback.
  • Optimize real-time perception pipelines for low-latency and robust performance in dynamic environments.
  • Work closely with hardware engineers to design sensor configurations and optimize perception models for onboard deployment.
  • Contribute to our broader AI and autonomy stack, ensuring seamless integration with reasoning, manipulation, planning and control.
  • Collaborate across disciplines to ensure seamless integration of ML models and provide technical mentorship to junior engineers.
Qualifications
Must-have:
  • MS or PhD in machine learning, computer science, robotics, or a related field.
  • Strong background in computer vision, deep learning, and sensor fusion.
  • Proficiency in Python and C++, with experience in frameworks like PyTorch, TensorFlow, OpenCV, and ROS.
  • Hands-on experience with real-world robotics perception systems (e.g., SLAM, 3D reconstruction, multimodal perception).
  • Experience working with hardware, including setting up and calibrating cameras, LiDAR, and other sensors.
  • Experience with data collection, preprocessing, and management in the context of training ML models.
  • Self-starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions.
  • Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics.

Nice-to-have:
  • Familiarity with robotic simulation environments (e.g., Gazebo, MuJoCo) and experience in sim-to-real transfer.
  • Experience in:
    • Developing models that can handle noisy, incomplete, or sparse data.
    • Deployment of ML models to edge devices for real-time inference (e.g., NVIDIA Jetson).
    • Accelerating ML training processes using GPU, TPU, or other HW accelerators.
    • General knowledge of robotics principles, including kinematics, dynamics, and control.