Senior Reality Capture Engineer, Robotics Hardware
Quick Summary
Propose custom sensor solutions when needed, assessing whether COTS (commercial off-the-shelf) choices are truly optimal or whether custom LiDAR or multi-camera systems perform better. 2.
The Hardware Team at FieldAI develops perception and compute payloads that power autonomous robotics systems in complex real world environments. Our work spans the full hardware stack designing and integrating sensing systems (LiDAR, camera, TOF, IMU, GPS), embedded compute (CPUs, GPUs, microcontrollers, Linux, ROS), electrical systems (power distribution, communication), and mechanical components (structures, thermal regulation, ingress protection). The team focuses on both development (research, design, prototyping, testing) and operations (production, testing, QA, debugging). We’re a small, fast-moving team, and we care deeply about improving: 1) core capabilities, 2) system reliability, 3) system scalability. As a growing team we are also building operational systems
and procedures from the ground up.
In this role on the Hardware Team at FieldAI, you will deliver the sensor modules that turn our robots into data-collection platforms for customers. This spans sensor selection, calibration, electro-mechanical integration, validation, and the data pipelines that carry sensor output from capture through processing. Examples of sensor modules include high-resolution LiDAR scanners, PTZ and thermal cameras, depth cameras, GNSS/RTK, and gas detection sensors. Candidates should be familiar with concepts and workflows such as laser scanning, photogrammetry, digital twins, BIM, and deviation and change analysis.
You will collaborate with the product team to select the right sensor for customers from hard industries such as construction and manufacturing. You will work closely with mechanical and electrical engineers to integrate each sensor into swappable modules on our robotic platform. You will own sensor performance such as calibration and time sync. As well as validate results through vibration and shock testing, point cloud evaluation, and other data quality checks. You may also lead the development of new custom reality capture sensors such as multicamera systems.
1. Sensor Selection & Cross-Team Coordination
Requirements
~1 min read-
Systems-Level Optimization: Act as the systems-level owner who prevents siloed, locally-optimized solutions, finding the truly optimal fix across domains.
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Cross-Disciplinary Coordination: Serve as the connective point between Autonomy, Insights, Mechanical, and Electrical, keeping sensor payload decisions aligned across the organization.
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Team Leadership & Roadmap: Oversee and mentor junior mechanical and electrical engineers, and contribute to sensor and hardware roadmap and vendor strategy.
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Education: B.S., M.S., or Ph.D. in Mechanical Engineering, Electrical Engineering, Robotics, or a related field.
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Experience Level: We're targeting 9+ years of experience for a senior to staff-level role, though we may consider more junior candidates with the right profile.
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Cross-Domain Engineering: Strong foundation across mechanical design, electrical design, and sensor hardware, with the breadth to work across all three.
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Data & Signal Processing Fluency: Working knowledge of point cloud and signal processing sufficient to evaluate software-based solutions to hardware problems.
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Systems-Level Optimization: Demonstrated ability to work across engineering domains and drive system-level, not just component-level, optimization.
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Sensor Knowledge: Deep familiarity with the sensor and geospatial-intelligence landscape, including LiDAR, cameras, thermal imaging, and gas detection.
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Mechatronics & Integration: Experience with electromechanical integration, mounting, enclosures, IP ratings, and connectors for ruggedized sensor payloads.
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Cross Functional Communication: Strong communicator able to arbitrate between teams that each see only their own piece of the solution space.
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Leadership: Experience managing or mentoring junior engineers on detailed design execution.
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Sensor Depth: Direct experience with sensors such as LiDAR, gas detection, thermal imaging, or PTZ camera systems.
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Field Robotics: Experience working with field robots subject to vibration, shock, or harsh environmental conditions such as construction or industrial sites.
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Mapping & Reality Capture: Familiarity with point cloud registration, photogrammetry and reconstruction, digital twin and BIM workflows, and deviation or change detection for environment mapping.
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Reality Capture Ecosystem: Familiarity with laser scanning hardware (FARO, Leica, Trimble) and reality-capture software platforms, applied to building or infrastructure inspection, construction verification, and asset management.
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Industry Exposure: Experience in construction, manufacturing, industrial, mining, or oil and gas environments, including hazardous-area (ATEX, IECEx, Class I Div 1/2) considerations.
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Research to Production: Experience taking sensor or perception work from research and algorithm development through to production deployment.
Location & Eligibility
About this job
- Pay per year
- $150,000–$250,000 a year
- 196% above the $67,500 median for Other jobs on Jobera (139,609 salaries).
- Who can apply
- United States
- Posted
- 113 days ago
Listing Details
- Posted
- July 20, 2026
- First seen
- July 20, 2026
- Last seen
- November 10, 2026
Posting Health
- Days active
- 112
- Repost count
- 0
- Trust Level
- 42%
- Scored at
- November 10, 2026
Signal breakdown
Field AI develops field-proven embodied artificial intelligence (AI) technology, specifically Field Foundation Models™ (FFMs), to enable robots to operate autonomously in complex, real-world environments across various industries.
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