Computer Vision Engineer

About the Role:

The Engineer III Computer Vision & Machine Learning role is a senior, hands-on position focused on developing and deploying perception and learning systems for autonomous UAVs. The role requires strong practical experience in computer vision, deep learning, and real-time deployment on embedded platforms.

The engineer will take technical ownership of vision and ML pipelines and work closely with the robotics team.

This role is ideal for engineers who enjoy taking algorithms from research to real-life deployment.

Key Responsibilities:

• Design, develop, and deploy computer vision and machine learning algorithms for autonomous UAV perception.
• Build and manage datasets and data pipelines, including data collection during flight tests, annotation, augmentation, training, and evaluation workflows.
• Ensure robust runtime behaviour under real-world conditions such as motion blur, lighting variation, and sensor noise.
• Optimize models and perception pipelines for real-time performance on embedded compute platforms, accounting for memory, latency, and power constraints.
• Integrate vision and ML outputs with robotics and autonomy stacks to enable downstream tasks such as navigation, obstacle avoidance, mapping, and decision-making.
• Document system designs, experiments, model performance, and deployment workflows to support maintainability and knowledge sharing.

Basic Requirements:

• Bachelors or Masters degree in Computer Science, Robotics, Artificial Intelligence, or Electrical Engineering.
• 1+ years (Masters) or 3+ years (Bachelors) of industry experience in computer vision, machine learning, or robotics-related roles.
• Strong hands-on experience with deep learning architectures such as CNNs, RNNs, and transformer-based models for vision tasks.
• Experience with image enhancement techniques such as denoising, deblurring, contrast enhancement, and low-light image improvement.
• Proficiency in Python and C++ for algorithm development and deployment.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Solid understanding of Image Processing, Linear Algebra, and Optimization Fundamentals.
• Experience working in Linux-based development environments.
• Strong debugging, analytical, and problem-solving skills.

Preferred Requirements:

• Experience optimizing inference using TensorRT, CUDA, or hardware accelerators.
• Experience designing teacher-student frameworks and applying knowledge distillation to balance accuracy, latency, and power constraints.
• Hands-on experience with deep learningbased object detection models (e.g., single-stage and two-stage detectors) for real-world vision tasks.
• Experience with multi-object tracking approaches, including learning-based tracking and data association techniques.
• Hands-on experience with spatial and frequency-domain filtering, including smoothing, edge-preserving, and sharpening filters.
• Experience working with UAVs, or autonomous robotic platforms.
• Hands-on experience deploying models on embedded edge platforms.
• Experience with ROS/ROS2 or robotics middleware.
• Experience with multi-sensor fusion involving vision and IMU.

Working Hours

• Standard working hours are 9:30 AM to 6:30 PM, Monday to Friday.
• Field-testing activities may require early-morning or extended hours, depending on mission requirements.

Compensation Range

• Competitive compensation aligned with industry standards, including performance-based incentives.
• Exact salary ranges can be customised according to experience.

Benefits

• Comprehensive health insurance.
• Professional development support.
• Detachment allowance.