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FieldAI

Robotics AI Engineer, Sensor Calibration

Irvine, California, United States

Location
Irvine, California, United States
Work
On-site
Employment
Full-time
Level
Not stated
Function
Data & AI
Pay
Not stated
Posted
3 months ago

About the role

Robotics AI Engineer – Sensor Calibration

About Field AI

Field AI is at the forefront of robotic embodied AI, transforming industries like construction, security, mining, and manufacturing. Our autonomous robots operate globally, often in harsh environments, delivering critical insights to customers. Whether monitoring construction progress, ensuring safety compliance, or conducting predictive maintenance, Field AI is advancing technology to make a meaningful impact.

Learn more at https://fieldai.com.

About the Job

Field AI is seeking a Robotics AI Engineer to help advance the sensor calibration systems that power our autonomous robots. As a member of our Calibration, Localization, and Mapping (CLAM) team, you will work alongside a highly focused group of engineers developing production-grade calibration pipelines for complex multi-sensor robotic platforms. Your work will span camera, LiDAR, IMU, and other sensor modalities, contributing to intrinsic, extrinsic, and temporal calibration workflows that enable reliable perception in real-world environments. Depending on your experience and interests, you'll improve automated calibration tooling, optimize large-scale sensor data processing, and develop robust calibration algorithms that support our downstream localization, mapping, and autonomy systems. The ideal candidate combines a strong foundation in robotics, computer vision, and 3D geometry with the practical engineering skills needed to build scalable, maintainable software in a fast-paced, collaborative environment.

What You Get To Do

  • Develop and refine sensor calibration workflows for various sensor modalities (e.g., LiDAR, cameras, IMUs), including intrinsic, extrinsic and temporal calibration in online and offline settings.
  • Design and implement scalable systems to manage and process large sensor datasets for calibration purposes, ensuring high reliability and performance.
  • Implement and optimize algorithms in C++ and Python, maintaining a clean and organized code base.
  • Explore and integrate emerging technologies and tools to enhance sensor calibration workflows.
  • Collaborate with cross-functional teams to meet project-specific documentation requirements and deliverables.

What You Have

  • Master’s degree in Computer Science, Engineering, or a related field.
  • 2+ years of work experience as a robotics software engineer, with expertise in robotics, computer vision and sensor calibration.
  • Proficiency in C++ and Python, with a proven ability to write maintainable and efficient code.
  • Solid background knowledge of 3D geometry and computer vision.
  • Solid understanding of sensor calibration techniques (e.g., camera intrinsic calibration, LiDAR-Camera calibration, multi-sensor extrinsic calibration).
  • Hands-on experience with sensor data processing tools and libraries such as PCL, Open3D, OpenCV, Kalibr, etc.
  • Familiarity with Robot Operating System (ROS) and software development practices in Ubuntu.
  • Familiarity with backend optimization tools and libraries such as Ceres, GTSAM, g2o.
  • Strong problem-solving skills, attention to detail, and able to work independently while managing multiple priorities.
  • Strong work ethic, highly self-motivated, and excellent written and verbal communication skills.

The Extras That Set You Apart

  • Ph.D. in Computer Science, Engineering, or a related field.
  • Research experience with publications in top-tier conferences or journals related to robotics, computer vision or machine vision.
  • Familiarity with factory-level calibration procedures and tooling for high-volume product lines (e.g., drones, autonomous vehicles, AR/VR devices).
  • Hands-on experience calibrating hundreds of camera intrinsics or camera-LiDAR systems at scale, including automated or semi-automated workflows.

Why Join Field AI?

We are solving one of the world’s most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment.

You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field, winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals.

Be Part of the Next Robotics Revolution

To tackle such ambitious challenges, we need a team as unique as our vision — innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We’re seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators.

We are headquartered in always-sunny Irvine, Southern California and have US based and global teammates.

Join us, shape the future, and be part of a fun, close-knit team on an exciting journey!

We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.

Source

Posted by FieldAI on their own hiring page, jobs.lever.co. OptiTalent shows it as published, read 07 Nov 2026 01:39 UTC; the original is the reference.

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