Computer Vision Engineer

Omnipresenttech; India; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Omnipresenttech is seeking a Computer Vision Engineer to design and deploy perception systems for drones operating in challenging environments. You will develop robust algorithms, fuse multi-sensor data, and optimize real-time onboard vision solutions for reliable autonomous flight.

The role requires strong CV expertise, Python/C++ programming, and hands-on experience with ROS and GPU-accelerated vision. Collaborative cross-team work and thorough documentation are essential.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical/Electronics Engineering, or related field.
• Strong experience with computer vision algorithms (OpenCV, visual odometry, SLAM, object detection).
• Proficient in Python and C++; embedded or GPU-accelerated vision is a plus.
• Practical experience in drone, UAV, or robotic vision systems.
• Understanding of sensor fusion for multi-modal data integration.
• Excellent analytical, problem-solving, and communication skills.

Responsibilities

• Develop and implement computer vision algorithms for real-time drone localization, mapping, and navigation.
• Work on visual odometry, optical flow, and SLAM for autonomous flight.
• Integrate and fuse vision data with IMU, LiDAR, and other onboard sensors for pose estimation.
• Optimize perception algorithms for embedded, resource-constrained platforms.
• Collaborate with autonomy and flight controls teams for system-level integration.
• Evaluate and calibrate camera and sensor configurations for challenging environments.
• Conduct simulation-based and real-world testing to validate performance.
• Stay updated on CV advancements and bring innovations to project solutions.
• Maintain clear technical documentation, test plans, and reports.

Skills

Computer vision algorithms

OpenCV

Visual odometry

SLAM

Object detection

Python

C++

Sensor fusion

Embedded vision

Education

Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical/Electronics Engineering

Tools

ROS

CUDA

TensorRT

ONNX

Job description

The Computer Vision Engineer will develop, test, and deploy visual navigation systems for drones operating in challenging environments. The role involves designing robust perception algorithms, fusing multi-sensor data, and optimizing vision-based solutions for real-time, onboard execution.

Key Responsibilities

• Develop and implement computer vision algorithms for real-time drone localization, mapping, and navigation in challenging situations.
• Work on visual odometry, optical flow, and SLAM (Simultaneous Localization and Mapping) for reliable autonomous flight.
• Integrate and fuse vision data with IMU, LiDAR, and other onboard sensors for accurate pose estimation
• Optimize perception algorithms for deployment on embedded, resource-constrained platforms.
• Collaborate with the autonomy and flight controls teams to ensure system-level integration and robust field performance.
• Evaluate, select, and calibrate camera and sensor configurations for challenging environments.
• Conduct simulation-based and real-world testing to validate performance in diverse scenarios.
• Stay updated on advancements in computer vision and bring relevant innovations into project solutions.
• Maintain clear technical documentation, test plans, and reports.

Required Qualification

• Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical/Electronics Engineering, or a related field.
• Strong experience with computer vision algorithms (OpenCV, visual odometry, optical flow, SLAM, object detection).
• Proficient programming skills in Python and C++; experience with embedded or GPU-accelerated vision (CUDA, TensorRT, ONNX) is a plus.
• Practical experience in drone, UAV, or robotic vision systems.
• Understanding of sensor fusion for multi-modal data integration.
• Excellent analytical, problem-solving, and communication skills.

Desired Skills

• Background in deep learning applied to perception tasks.
• Familiarity with robotics middleware (e.g., ROS), simulation environments, and hardware-in-the-loop testing.
• Knowledge of edge-AI deployment models, code optimisation, and real-time architecture.
• Experience in collaborative, multidisciplinary engineering environments.
• Proven track record of writing and maintaining well-documented code and technical documentation.