3D SLAM Engineer

Role Summary
We are looking for a SLAM Engineer to develop advanced real-time mapping, tracking, and localization technologies for next-generation spatial intelligence systems. You will work on the core algorithms behind 3D reconstruction, multi-sensor fusion, and robust tracking for robotics, AR/XR, and industrial automation.

Key Responsibilities1. Core SLAM Algorithm Development

• Design and implement visual, visual-inertial (VIO), RGB-D, and LiDAR SLAM systems.
• Develop modules for:
• Feature extraction and matching
• Keyframe selection
• Loop closure and global optimization
• Bundle adjustment, pose graph optimization
• Improve SLAM robustness under dynamic, low-light, reflective, or textureless environments.

2. 3D Reconstruction & Mapping

• Build pipelines for dense mapping, volumetric fusion (TSDF/ESDF), point cloud processing, and mesh generation.
• Optimize real-time reconstruction for mobile, robotics, and wearable devices.

3. Sensor Fusion

• Integrate and calibrate IMUs, stereo cameras, depth sensors, LiDARs, and wheel odometry.
• Implement EKF/UKF, factor graph optimization, and tightly-coupled fusion architectures.

4. Performance Optimization

• Optimize SLAM for real-time operation on edge devices: GPU, NPU, FPGA, embedded boards (Jetson, Qualcomm, Rockchip, M-series).
• Apply model and algorithmic acceleration: parallelization, SIMD, TensorRT, CUDA, VPI.

5. Systems Integration

• Integrate SLAM into robotic navigation stacks, AR/XR applications, and 3D capture systems.
• Work with ROS/ROS2, real-time streaming, and multi-threaded processing pipelines.
• Validate performance in real field environments (construction, manufacturing, robotics labs).

Required Qualifications

• BS/MS/PhD in Robotics, Computer Vision, Electrical Engineering, or related field.
• Strong skills in C++, Python, and algorithms.
• Deep understanding of:
• Computer vision fundamentals (epipolar geometry, camera models)
• 3D geometry, linear algebra, numerical optimization
• Probabilistic state estimation (Kalman filters, factor graphs)
• Experience with libraries such as OpenCV, PCL, g2o, Ceres Solver, Open3D.

Preferred Experience

• Experience building SLAM systems from scratch (VSLAM, VIO, RGB-D SLAM, LiDAR SLAM).
• Familiarity with ORB-SLAM, OKVIS, ROVIO, VINS-Fusion, RTAB-Map.
• Experience with GPU compute (CUDA), FPGA acceleration, or embedded optimization.
• Background in robotics navigation, AR/XR spatial mapping, or 3D scanning.
• Experience with large-scale mapping, multi-camera rigs, or high-precision 3D capture (<1 mm error systems).

Job Type: Full-time

Pay: ₹1,500,000.00 - ₹3,000,000.00 per year