Computer Vision Engineer

Key Responsibilities

• Develop vision and 3D perception algorithms using deep learning and geometric methods.
• Work with point clouds, depth data, and multimodal fusion (camera + LiDAR).
• Build and maintain calibration pipelines (camera, LiDAR, IMU).
• Implement production-quality code in C++ and Python.
• Optimize models for real-time or embedded platforms (quantization, pruning, GPU tuning).
• Deploy and maintain inference pipelines for cloud or edge devices.
• Collaborate across teams to integrate perception into production systems.

Required Qualifications

• Strong background in computer vision, deep learning, or 3D perception.
• Experience with CNNs, transformers, and point cloud/3D vision methods (stereo, depth, SLAM).
• Proficiency in Python and C++ for algorithm and system development.
• Hands-on calibration experience (intrinsic/extrinsic, LiDAR-camera, IMU).
• Experience with PyTorch or TensorFlow.
• Model optimization and deployment on GPUs or embedded devices (Jetson, ARM, accelerators).

Preferred Qualifications

• Master’s or PhD in Computer Vision, Robotics, ML, or related fields.
• Experience with sensor fusion frameworks and spatial AI systems.
• Background in robotics, mapping, or edge perception systems.
• Familiarity with MLOps or large-scale deployment workflows.

What We Offer

• Opportunities to work on advanced 2D/3D perception and multimodal AI.
• Ownership of production-grade, real-time vision systems.
• A collaborative engineering and research‑driven environment.
• Competitive compensation and technical growth opportunities.