Advanced Engineer - Technology Development-Computer Vision

Technology, Data & Digital · Software & Web Development · Software Engineering · Data Science · Artificial Intelligence

In short

Autoliv is seeking a Senior Engineer / Advanced Engineer - Technology Development-Computer Vision in Bangalore to develop next-generation perception technologies. This role involves cutting-edge research and practical engineering for production-ready computer vision solutions using monocular and stereo imaging systems, focusing on 3D understanding, localization, mapping, and scene interpretation.

Responsibilities

Design, develop, and optimize computer vision solutions using monocular and stereo camera systems.
Build and validate 3D localization, mapping, SLAM (Simultaneous Localization and Mapping), and VINS (Visual Inertial Navigation System) pipelines.
Develop algorithms for 3D reconstruction, multi-view geometry, depth estimation, camera pose estimation, and scene understanding.
Perform camera modeling and calibration for pinhole, fisheye, and stereo vision systems.
Apply classical computer vision techniques and deep learning-based approaches for perception applications.
Develop data preprocessing, feature engineering, and model evaluation pipelines.
Implement and optimize solutions using Python, C++, OpenCV, and Point Cloud Library (PCL).
Deploy, monitor, and improve AI/ML solutions on Linux-based systems and cloud platforms such as Azure ML Studio.
Analyze performance bottlenecks, debug issues, and continuously improve solution robustness and accuracy.
Collaborate with cross-functional engineering teams to translate research concepts into scalable products.

Requirements

Monocular and Stereo Vision Systems
Multi-view Geometry
Camera Calibration
3D Reconstruction
Depth Estimation
Scene Understanding
Visual Localization
Human Pose Estimation
CNN-based Object Detection
Depth Estimation Networks
Human Pose Estimation Models
Model Evaluation & Validation
Data Annotation and Dataset Development
Python
C++
OpenCV
Point Cloud Library (PCL)
NumPy
Pandas
Linux Development Environment
Azure ML Studio
Cloud-based ML Workflows
Model Deployment and Monitoring

Desired Qualifications

Developing computer vision applications for real-world deployment.
Building and deploying SLAM, VINS, or localization systems.
Camera calibration and stereo vision pipeline development.
3D mapping and reconstruction technologies.
Working with deep learning models such as: Depth Anything, OpenPose, Object Detection Frameworks.
End-to-end AI/ML model development and deployment on cloud platforms.

Benefits

International work setting
Opportunities designed to enhance career and personal development
New and different perspectives ensure team success
Commitment to developing people’s skills, knowledge and creative potential
Training and development programs emphasize technical competency, leadership development and business management skill

Skills

PythonC++OpenCVPoint Cloud Library (PCL)NumPyPandasLinuxAzure ML StudioMonocular and Stereo Vision SystemsMulti-view GeometryCamera Calibration3D ReconstructionDepth EstimationScene UnderstandingVisual LocalizationHuman Pose EstimationCNN-based Object DetectionSLAMVINS

#Computer Vision#Technology Development#Perception Technologies#3D Understanding#Localization#Mapping#Scene Interpretation#Monocular Imaging#Stereo Imaging#Multi-view Geometry#Sensor Calibration#SLAM#VINS#Deep Learning#3D Reconstruction#Python#C++#OpenCV#PCL#Azure ML Studio

About Autoliv

Autoliv, Inc. is the worldwide leader in automotive safety systems. We develop, manufacture and market protective systems, such as airbags, seatbelts, steering wheels and pedestrian protection systems for all major automotive manufacturers in the world. Our products save 37,000 lives and prevent 450,000 injuries each year. Our ~65,000 employees in 25 countries are passionate about our vision of Saving More Lives and quality is at the heart of everything we do. We have 13 technical centers, with 20 test tracks. In the world of automotive occupant safety, we were the first to introduce the two-…

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