포지션 상세
This position is with STRADVISION Seoul Office.
[About STRADVISION]
We Empower Everything To Perceive Intelligently
With a mission statement of “We Empower Everything To Perceive Intelligently”, STRADVISION is putting all of our effort to make better life for everyone through AI-based camera perception technology. Everyday, we focus on creating AI-based vision perception techonolgy with more than 300 members across 8 offices worldwide and we expect our software to perceive everything precisely & intelligently to make 1% difference in people’s lives. Thus, we are looking for members who would like to join our meaningful journey and face challenges that no one has done it before together at STRADVISION.
[Our Story]
• STRADVISION's Core Technology : https://buly.kr/74XS8bi
• STRADVISION's Welfare : https://buly.kr/BpFucdd
[Our Technology]
STRADVISION's Technology : https://stradvision.com/dh/technology
• STRADVISION is the FIRST deep-learning based technology start-up company in the world who has obtained ASPICE CL2 certification in 2019.
• STRADVISION has also been honored with the AutoSens Awards for ‘Best-in-Class Software for Perception Systems’(Gold Award Winner) for 2 years in a row(2021, 2022).
• STRADVISION’s outstanding technology was recognized worldwide by successfully completing the Series C funding at KRW 107.6 billion with Aptiv and ZF Group in August, 2022.
• About 167 patents related to autonomous driving/ADAS have been acquired in Korea, Japan, US and Europe. As of today, STRADVISION is actively developing our technology to be differentiated.
• By the first half of 2025, vehicles equipped with SVNet surpassed 4 million units globally, maintaining growth despite economic slowdown and intensifying industry competition.
• In 2025, STRADVISION was ranked 10th in domestic AI competitiveness, following companies such as Samsung, Naver, and LG.
We are seeking a highly experienced Multi-Sensor Fusion SLAM Engineer with deep expertise in offline, high-precision trajectory estimation and 3D mapping for automotive applications. The ideal candidate will have more than 5 years of experience and strong domail knowledge in multi-sensor fusion SLAM, factor graph optimization, and large-scale batch processing.
This role will be responsible for developing centimeter-level accurate vehicle trajectory estimation and 3D point cloud map generation by fusing surround-view cameras, multi-type LiDARs(Spinning/Flash), high-rate IMU, wheel odometry, and GNSS data, with a focus on maximizing final output precision and reliability over real-time constraints.
[Key Responsibilities]
• Develope multi-sensor odometry modules(LiDAR-Inertial, visual) that produce robust initial trajectory estimates from heterogeneous sensor streams.
• Design and maintain a factor graph-based global optimization pipeline that fuses all sensor modalities - including loop closure, vehicle kinematic constraints, and GNSS anchoring - to deliver centimeter-level accurate trajectories via full-batch smoothing.
• Generate globally consistent, high-fidelity 3D point cloud maps from the optimized trajectories, ensuring static-environment integrity through dynamic object filtering.
• Build and maintain sensor data preprocessing pipelines covering raw data parsing, time synchronization, coordinate frame transformation, and quality assurance across all sensor channels.
• Define quantitative evaluation frameworks and systematically benchmark SLAM performance across diverse and challenging driving conditions.
• Collaborate with Sensor Integration, Data labeling, and Perception teams.
• 5+ years of experience in SLAM, state estimation, or multi-sensor fusion, preferably in the automotive or robotics industry.
• Strong theoretical foundation in probabilistic state estimation, nonlinear optimization, and 3D geometry (e.g., SE(3)/Lie group formulations), along with hands-on experience using optimization frameworks such as GTSAM, g2o, or Ceres Solver.
• Demonstrated expertise in LiDAR-based and visual SLAM methods, with the ability to tightly couple heterogeneous sensor modalities (LiDAR, camera, IMU, wheel odometry, GNSS).
• Proficiency in C++ and Python, with practical experience in large-scale point cloud processing libraries (PCL, Open3D).
[About STRADVISION]
We Empower Everything To Perceive Intelligently
With a mission statement of “We Empower Everything To Perceive Intelligently”, STRADVISION is putting all of our effort to make better life for everyone through AI-based camera perception technology. Everyday, we focus on creating AI-based vision perception techonolgy with more than 300 members across 8 offices worldwide and we expect our software to perceive everything precisely & intelligently to make 1% difference in people’s lives. Thus, we are looking for members who would like to join our meaningful journey and face challenges that no one has done it before together at STRADVISION.
[Our Story]
• STRADVISION's Core Technology : https://buly.kr/74XS8bi
• STRADVISION's Welfare : https://buly.kr/BpFucdd
[Our Technology]
STRADVISION's Technology : https://stradvision.com/dh/technology
• STRADVISION is the FIRST deep-learning based technology start-up company in the world who has obtained ASPICE CL2 certification in 2019.
• STRADVISION has also been honored with the AutoSens Awards for ‘Best-in-Class Software for Perception Systems’(Gold Award Winner) for 2 years in a row(2021, 2022).
• STRADVISION’s outstanding technology was recognized worldwide by successfully completing the Series C funding at KRW 107.6 billion with Aptiv and ZF Group in August, 2022.
• About 167 patents related to autonomous driving/ADAS have been acquired in Korea, Japan, US and Europe. As of today, STRADVISION is actively developing our technology to be differentiated.
• By the first half of 2025, vehicles equipped with SVNet surpassed 4 million units globally, maintaining growth despite economic slowdown and intensifying industry competition.
• In 2025, STRADVISION was ranked 10th in domestic AI competitiveness, following companies such as Samsung, Naver, and LG.
주요업무
[Mission of the Role]We are seeking a highly experienced Multi-Sensor Fusion SLAM Engineer with deep expertise in offline, high-precision trajectory estimation and 3D mapping for automotive applications. The ideal candidate will have more than 5 years of experience and strong domail knowledge in multi-sensor fusion SLAM, factor graph optimization, and large-scale batch processing.
This role will be responsible for developing centimeter-level accurate vehicle trajectory estimation and 3D point cloud map generation by fusing surround-view cameras, multi-type LiDARs(Spinning/Flash), high-rate IMU, wheel odometry, and GNSS data, with a focus on maximizing final output precision and reliability over real-time constraints.
[Key Responsibilities]
• Develope multi-sensor odometry modules(LiDAR-Inertial, visual) that produce robust initial trajectory estimates from heterogeneous sensor streams.
• Design and maintain a factor graph-based global optimization pipeline that fuses all sensor modalities - including loop closure, vehicle kinematic constraints, and GNSS anchoring - to deliver centimeter-level accurate trajectories via full-batch smoothing.
• Generate globally consistent, high-fidelity 3D point cloud maps from the optimized trajectories, ensuring static-environment integrity through dynamic object filtering.
• Build and maintain sensor data preprocessing pipelines covering raw data parsing, time synchronization, coordinate frame transformation, and quality assurance across all sensor channels.
• Define quantitative evaluation frameworks and systematically benchmark SLAM performance across diverse and challenging driving conditions.
• Collaborate with Sensor Integration, Data labeling, and Perception teams.
자격요건
[Basic Qualifications]• 5+ years of experience in SLAM, state estimation, or multi-sensor fusion, preferably in the automotive or robotics industry.
• Strong theoretical foundation in probabilistic state estimation, nonlinear optimization, and 3D geometry (e.g., SE(3)/Lie group formulations), along with hands-on experience using optimization frameworks such as GTSAM, g2o, or Ceres Solver.
• Demonstrated expertise in LiDAR-based and visual SLAM methods, with the ability to tightly couple heterogeneous sensor modalities (LiDAR, camera, IMU, wheel odometry, GNSS).
• Proficiency in C++ and Python, with practical experience in large-scale point cloud processing libraries (PCL, Open3D).
