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Perception Algorithm Engineer Jobs (NOW HIRING)

Teleo

Lead Perception Engineer

Palo Alto, CA · On-site

$120K - $158K/yr

Build perception algorithms and architecture, fusing multiple sensor modalities and supporting an ... S. or higher in Computer Science, Computer Engineering, Robotics, Electrical Engineering, or a ...

Teleo

Lead Perception Engineer

Palo Alto, CA

$120K - $158K/yr

Build perception algorithms and architecture, fusing multiple sensor modalities and supporting an ... S. or higher in Computer Science, Computer Engineering, Robotics, Electrical Engineering, or a ...

ISEE

Senior Perception Engineer

$107K - $146K/yr

ISEE is seeking an experienced full-time Senior Perception Engineer to join our team. Job duties ... Specifically: • Research, design, and develop algorithms for autonomous driving systems to solve ...

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Perception Algorithm Engineer information

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How much do perception algorithm engineer jobs pay per year?

As of Jun 19, 2026, the average yearly pay for perception algorithm engineer in the United States is $111,632.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,500.00 and $132,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Perception Algorithm Engineer, you need a strong background in computer vision, machine learning, and programming (typically C++ or Python), often supported by a degree in computer science, robotics, or a related field. Familiarity with tools like TensorFlow, PyTorch, OpenCV, and ROS, as well as experience with sensor data (e.g., LiDAR, cameras), is crucial. Strong analytical thinking, problem-solving abilities, and effective teamwork are standout soft skills for this role. These skills are vital to develop robust perception systems that enable autonomous vehicles and robots to interpret and interact safely with complex real-world environments.

What is a Perception Algorithm Engineer?

A Perception Algorithm Engineer is a professional who develops algorithms that enable machines—such as autonomous vehicles or robots—to interpret and understand sensory data from their environment. This typically involves processing data from cameras, lidar, radar, and other sensors to identify objects, track movement, and understand surroundings. Perception Algorithm Engineers work with computer vision, sensor fusion, and machine learning techniques to create reliable and efficient perception systems. Their work is crucial in making machines aware of their surroundings and enabling them to respond appropriately. They often collaborate with hardware, software, and robotics teams to integrate their algorithms into real-world applications.

What are some common challenges faced by Perception Algorithm Engineers when integrating their solutions into autonomous systems?

Perception Algorithm Engineers often encounter challenges when ensuring their algorithms perform reliably in diverse real-world environments, such as varying lighting, weather conditions, and sensor noise. Integrating algorithms with hardware requires close collaboration with robotics and systems engineering teams to optimize performance and latency. Additionally, balancing accuracy with computational efficiency is crucial, as perception modules must run in real time on embedded systems. Addressing these challenges involves rigorous testing, continuous model improvement, and effective cross-functional communication.
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Perception Algorithm Engineer jobs near you
Infographic showing various Perception Algorithm Engineer job openings in the United States as of June 2026, with employment types broken down into 9% Locum Tenens, 55% Full Time, 27% Part Time, and 9% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $111,632 per year, or $53.7 per hour.

Autonomy Algorithm Engineer, Planning & Prediction

Bot Auto

Houston, TX • On-site

Full-time

Posted 18 days ago

Job description

Company Introduction
At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a startup and the wisdom of seasoned experts, our team has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create groundbreaking solutions that propel the future of transportation. Join us and transform your ideas into reality.
About The Role
You will design and ship the algorithms that decide how our trucks move. This spans classical motion planning and behavior, a growing learning-based prediction and planning pipeline, and the online mapping and map-building layer that planning depends on. You will work end to end - from problem framing and algorithm design through implementation, on-vehicle validation, and the cases that come back from the road. This is a hands-on engineering role for someone who wants their work driving real freight on public highways.
What You'll Do
  • Develop and improve motion planning and behavior algorithms for highway and surface-street driving.
  • Build the learning-based pipeline for prediction and planning: data curation, model design and training, and integration on-vehicle.
  • Advance online mapping and map-building, and the real-time map signals that planning consumes.
  • Turn road and simulation cases into root-cause analysis, algorithmic fixes, and regression coverage that prevents recurrence.
  • Collaborate across perception, control, simulation, and operations to take features from design through validated release.
Required Qualifications
  • B.S. or M.S. in Computer Science, Robotics, Electrical Engineering, Applied Math, or a related field, or equivalent practical experience.
  • 2+ years building production algorithms in robotics, autonomous vehicles, or a comparable real-time system.
  • Strong C++ and Python; comfortable owning performance-sensitive code that runs on-vehicle.
  • Solid foundation in at least one of: motion planning and optimization, prediction/behavior modeling, or mapping.
  • A track record of shipping algorithms that ran on real hardware or in production, not only in research or simulation.
Preferred Qualifications
  • Experience with learning-based components in a planning or prediction stack (sequence/trajectory models, imitation or reinforcement learning, model training and deployment pipelines, GPU inference in a real-time loop).
  • Experience with online/HD mapping, reference-line or lane-graph generation.
  • Familiarity with the planning-perception interface: uncertainty representation, occlusion reasoning, safety and liability evaluation, and agent modeling.
  • Experience operating in a safety-critical or heavily validated software environment.
  • Background in autonomous trucking or highway-speed autonomy.

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