Computer Vision Engineer

About the Role

We are looking for a talented Computer Vision Engineer to design, implement, and deploy advanced vision-based systems that power real-world applications. This role offers the opportunity to work with cutting-edge deep learning models and collaborate with experts across multiple domains.

Key Responsibilities

• Design and develop computer vision algorithms for object detection, segmentation, tracking, pose estimation, and more.
• Implement and optimize deep learning models using PyTorch, TensorFlow, and OpenCV.
• Prepare datasets, conduct model training, fine-tuning, and performance evaluation on real-world data.
• Deploy computer vision models to cloud and edge environments using tools like ONNX, TensorRT, and Docker.
• Collaborate with backend and infrastructure teams to integrate vision models into scalable applications.
• Stay up to date with the latest research in computer vision and apply relevant findings to production.
• Participate in code reviews, contribute to architecture design, and help maintain high-quality technical documentation.

Required Qualifications

• Bachelors or Masters degree in Computer Science, Electrical Engineering, or a related field.
• 2-4 years of professional experience in computer vision and deep learning.
• Proficiency in Python and/or C++, with solid experience using PyTorch, TensorFlow, and OpenCV.
• Strong understanding of CNNs, vision transformers, and modern computer vision architectures.
• Familiarity with model optimization and compression techniques.
• Hands-on experience with deployment tools such as Docker, REST APIs, ONNX, and TensorRT.

Nice to Have

• Experience with edge deployment on devices like Jetson Nano, Coral, or mobile platforms.
• Exposure to MLOps tools, CI/CD for ML pipelines, or cloud platforms (AWS, Azure, GCP).
• Familiarity with SLAM, OCR, 3D vision, or multimodal ML approaches.

Whats Offered

• Above industry-standard compensation packages.
• Comprehensive medical insurance coverage.
• Funding for higher studies and professional qualifications.
• Opportunities for rapid career growth in a global and innovation-driven environment.
• Remote-first, flexible work setup that values autonomy and creativity.