Computer Vision Engineer

Amazin Automation Solutions India; Gurugram District; On-site; INR 1,200,000 - 2,500,000; Full time

Job summary

Amazin Automation Solutions India invites an experienced Computer Vision Engineer to design and deploy 2D/3D vision and LiDAR based systems for industrial environments. You will work on sensor data acquisition, processing, and real-time deployment on edge devices, collaborating with robotics and automation teams.

The role demands hands-on LiDAR and CV expertise and cross-team integration.

Qualifications

• Strong Python programming skills.
• Hands on experience with LiDAR sensors and point cloud data.
• Experience with OpenCV and camera LiDAR calibration.
• Experience developing production-ready CV applications.
• Experience with PyTorch and/or TensorFlow.
• Knowledge of 3D projection and coordinate systems.
• Hands on experience with multiple LiDAR sensors SDKs/drivers.
• Experience with edge deployment on NVIDIA Jetson or similar.

Responsibilities

• Develop CV solutions for image/video data including detection, classification, tracking, segmentation, OCR, ANPR, and defect detection.
• Process LiDAR point clouds: filtering, downsampling, ROI extraction, ground plane removal, clustering, measurement.
• Work with LiDAR sensors, SDKs, drivers, and data formats.
• Handle real-time sensor data streams with timing, loss, and health monitoring.
• Perform camera and LiDAR calibration and extrinsic/intrinsic calibration.
• Develop Camera-LiDAR fusion for localization, depth, and measurement.
• Train and evaluate CV/LiDAR models with metrics like precision, recall, mAP.
• Prepare and annotate datasets for CV and LiDAR models.
• Optimize CV/LiDAR pipelines for real-time performance on CPU/GPU/edge.

Skills

Python

C++

Linux (Ubuntu)

Computer Vision fundamentals

LiDAR understanding

Pytorch / TensorFlow

OpenCV

Camera calibration

Coordinate transformations

Sensor fusion

Edge deployment

CUDA (basic)

Real-time data processing

Object detection / tracking

3D perception

Education

Bachelor's or Master's degree in Computer Science, Electronics, Robotics, Engineering, or related field

Tools

Git

ROS/ROS2

YOLO or similar

TensorRT

NVIDIA Jetson or edge devices

Point cloud processing tools

Job description

Job Title

Computer Vision Engineer 2D/3D Vision & LiDAR

Job Summary

We are looking for a Computer Vision Engineer with hands on experience in building and deploying real world Computer Vision and LiDAR based systems.

The candidate will work on projects involving cameras, LiDAR sensors, 2D/3D vision, object detection, tracking, measurement, and sensor integration for industrial environments such as factories, warehouses, logistics, and robotic systems.

The role involves working on the complete pipeline from sensor data acquisition and processing to detection, measurement, calibration, 3D positioning, and real time deployment on edge devices.

The candidate should be comfortable working with real world and noisy sensor data and should have experience working with multiple LiDAR sensors technologies and their SDKs drivers, and data formats.

Key Responsibilities

• Develop Computer Vision solutions for image and video data, including object detection, classification, tracking, segmentation, OCR, ANPR, and defect anomaly detection.
• Process and analyze LiDAR point clouds for filtering, noise removal, downsampling, ROI extraction, ground plane removal, clustering, object detection, and measurement.
• Work with different LiDAR sensors, SDKs, drivers, and data formats.
• Handle real time sensor data streams, including data acquisition, timestamps, packet loss, reconnection, and sensor health monitoring.
• Perform camera calibration and LiDAR calibration, including intrinsic and extrinsic calibration.
• Work with different coordinate systems such as camera, LiDAR, robot, machine, and world coordinates, and perform transformations between them.
• Develop Camera LiDAR fusion solutions for localization, depth, and measurement.
• Develop solutions for distance, depth, object position, dimensions, and spatial measurements using cameras and LiDAR.
• Train, evaluate, and improve Computer Vision deep learning models using appropriate metrics such as precision, recall, mAP, localization error, and measurement accuracy.
• Prepare, clean, annotate, and manage datasets for Computer Vision and LiDAR based models.
• Optimize Computer Vision and LiDAR pipelines for real time performance on CPU GPU and edge devices.
• Design reliable failure handling so that the system can identify poor data, occlusion, low confidence, or sensor issues instead of producing unreliable results.
• Integrate Computer Vision LiDAR outputs with robotics, PLCs, and other software systems.
• Support system testing, deployment, commissioning, troubleshooting, and performance optimization in real world environments.
• Maintain clear technical documentation, test cases, and troubleshooting commissioning documentation.

Required Skills & Technologies

• Strong Python programming skills.
• Working knowledge of C++ is preferred, especially for performance critical applications.
• Good understanding of Git and Linux Ubuntu.
• Experience developing production ready Computer Vision applications.
• Strong understanding of Computer Vision fundamentals.
• Hands on experience with OpenCV.
• Image preprocessing, filtering, thresholding, edge detection, contours, morphology, feature matching, and geometric operations.
• Understanding of camera models, coordinate systems, transformations, and pose estimation.
• Hands on experience with PyTorch and/or TensorFlow.
• Experience with object detection frameworks such as YOLO or similar.
• Experience with Object Detection, Image Classification, Segmentation, Object Tracking.
• Knowledge of tracking algorithms such as SORT, DeepSORT, ByteTrack, or similar.
• Experience with model training, evaluation, optimization, and deployment.
• Knowledge of ONNX and/or TensorRT is preferred.
• Experience with OCR technologies.
• Experience processing real time camera video streams.
• Understanding of video decoding, frame processing, event detection, and real time video analytics.
• Understanding of 2D to 3D projection and 3D coordinate systems.
• Knowledge of depth and distance estimation.
• Experience with stereo cameras, depth cameras, or LiDAR for 3D perception.
• Understanding of rotation, translation, transformation matrices, and coordinate frame conversions.
• Hands on experience working with LiDAR sensors and point cloud data.
• Experience with multiple LiDAR sensors technologies and their SDKs or drivers.
• Experience with Point cloud filtering, Voxel downsampling, Outlier noise removal, ROI extraction, Ground plane segmentation, RANSAC, Clustering, 3D bounding boxes, Object measurement, Point cloud registration alignment.
• Understanding of LiDAR characteristics such as range, intensity, field of view, noise, and scan patterns.
• Knowledge of point cloud registration techniques such as ICP and rigid transformation estimation.
• Experience integrating cameras and LiDAR sensors.
• Understanding of Camera LiDAR calibration and sensor fusion.
• Experience deploying Computer Vision solutions on NVIDIA Jetson or similar edge devices is preferred.
• Basic understanding of CUDA and GPU based inference.

Required Experience

• 5 to 6 years of hands on experience in Computer Vision, with at least 2 to 3 years working directly with LiDAR.
• Practical experience working with LiDAR and point cloud data.
• Experience working with multiple LiDAR sensors technologies and their SDKs drivers, or data formats.
• Experience developing and deploying at least one real world Computer Vision, LiDAR, robotics, or industrial vision system.
• Experience with camera LiDAR calibration and coordinate transformations.
• Experience converting sensor measurements into real world dimensions, positions, distances, or coordinates.
• Experience testing, debugging, and improving systems using real world field data.
• Bachelor s or Master s degree in Computer Science, Electronics, Robotics, Engineering, or a related field, or equivalent practical experience.

Good to Have Skills

• Experience with ROS or ROS 2.
• Experience with 3D deep learning and point cloud models such as PointNet PointPillars, or similar.
• Experience with SLAM, mapping, or localization.
• Experience integrating Computer Vision LiDAR with industrial robots such as FANUC, ABB.
• Experience with multi sensor time synchronization.
• Experience with Docker and CI/CD.
• Experience with industrial cameras and machine vision systems.
• Experience building simple monitoring dashboards or interfaces for live camera LiDAR data.
• Knowledge of industrial safety concepts.
• Experience with logging, databases, and traceability systems.

Ideal Candidate Profile

The ideal candidate should be someone who can work across the complete Computer Vision + LiDAR pipeline, from sensor data acquisition and preprocessing to AI inference, 3D perception, calibration, sensor fusion, real time optimization, and deployment.

The candidate should have a strong hands on and problem solving approach and be comfortable working with real world industrial conditions, noisy sensor data, hardware limitations, and field deployment challenges.