Senior Software Engineer, SLAM/VIO

Rivet Industries, Inc.
San Jose, CA, United States
22 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Compensation
$210,000 - $300,000
Working hours
Regular working hours
Job source

Tech stack

Computer Vision C++ (Programming Language) Software Debugging Python (Programming Language) Sensor Fusion Real Time Systems Deployment Automation

Job description

We are building the perception stack that enables robust three/six degrees of freedom tracking, localization, and mapping in complex real-world environments. This role focuses on fusing data from cameras and inertial sensors to power SLAM / Visual-Inertial Odometry pipelines. We need an experienced perception software engineer who can create algorithms and systems that run in real time, handle uncertainty gracefully, and provide the foundation for advanced spatial intelligence on edge devices., * Develop and optimize sensor fusion algorithms combining IMU and camera data for SLAM and VIO (Simultaneous Localization and Mapping & Visual Inertial Odometry)

  • Implement state of the art structure-from-motion techniques using different sensor modalities to generate consistent 3D reconstructions
  • Evaluate algos against public benchmarks and real-world datasets
  • Integrate outputs into higher-level autonomy or collaborative mapping systems (i.e. shared mapping systems)
  • Collaborate with HW, robotics and platform teams to ensure end-to-end performance
  • Define metrics, testing frameworks and deployment strategies for production-ready perception systems

Requirements

  • BS with 10+ years of academic or industry experience in inertial sensing, computer vision, robotics or related fields with shipped or published work (or MS with 8+ yrs of the above)
  • Shipped SLAM/VIO features to product
  • Strong background in linear algebra, 3D geometry, VIO (probabilistic filtering and/or factor-graph optimization), and visual mapping (incremental mapping, submaps, loop closure)
  • Proficient in C++/Python with experience in real-time optimization
  • Proficient in using and debugging geometric optimization frameworks (e.g. Ceres, GTSAM, g2o)
  • Knowledge of sensor modelling, calibration and noise characteristics
  • Experience with real-time processing pipelines on embedded or edge hardware
  • Preferred track record of applied research in robotics or AR/VR

Benefits & conditions

Compensation may vary within the posted range based on relevant experience, skills, education, and other job-related factors. In addition to base salary, this role may be eligible for equity and other forms of compensation. Eligible employees also receive a competitive benefits package, including unlimited PTO.

Rivet is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable law. Certain roles may require U.S. Person status, security clearance eligibility, or other requirements imposed by law or government contract.

Compensation Range: $210K - $300K

About the company

About Rivet Rivet is an American company building integrated task systems - fusing hardened hardware with software, sensors, AI, and networking - for industrial workforces and defense personnel. We create capabilities that multiply the effectiveness of every individual and withstand the world’s toughest environments.

We serve the people who build, operate, maintain, and defend our way of life. From technicians and engineers to first responders and service members, they embody the hard work, ingenuity, and meritocratic values that drive Western prosperity. Yet too often they are forced to rely on outdated tools that fail under modern pressures. Rivet exists to reset that priority.

At Rivet, you’ll join a mission-driven team that fuses disciplines to deliver decisive outcomes where they matter most. Whether shaping our technology, strengthening our partnerships, or building our culture, every role here contributes to equipping the front lines with the modern systems they deserve.

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