Computer Vision Engineer

Role Overview

We need a passionate engineer to design, develop, and deploy advanced deep learning models and computer vision systems. You'll work in a fast-paced startup environment, handling multiple projects and making significant impact on cutting-edge AI solutions.

Key Responsibilities

Develop deep learning models for image classification, object detection, segmentation, and tracking

Build computer vision pipelines for real-time applications and automation systems

Research and implement cutting-edge AI techniques from research papers to production

Deploy and optimize models in cloud environments (AWS, GCP, Azure)

Work with large datasets and implement data augmentation techniques

Collaborate with cross-functional teams to integrate AI solutions into products

Monitor and maintain deployed models for optimal performance

Mentor junior developers and contribute to team growth

Required Skills

3-5 years experience in deep learning/computer vision

Expert Python proficiency with TensorFlow, PyTorch, Keras

Strong knowledge of OpenCV, computer vision algorithms

Experience with neural architectures (CNNs, YOLO, ResNet, Transformers)

Cloud deployment experience (AWS, GCP, Azure)

MLOps knowledge (Docker, Git, CI/CD pipelines)

Production model deployment experience

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

Preferred Qualifications

Experience with ROS, robotics applications

Knowledge of model optimization (quantization, pruning)

Edge deployment experience (TensorFlow Lite, ONNX)

Startup environment experience

Open-source contributions or published research

What We Offer

Professional development budget and conference attendance

Cutting-edge technology access and growth opportunities

Direct impact on product development and company direction

How to Apply

To apply for the Deep Learning& Computer Vision Engineer position, please fill out the application form using the link below. Make sure to provide accurate details, upload your updated resume, and include links to any past projects or portfolios.

Apply here:

https://forms.gle/J5bXUVWLBXKGjty7A