Deep Learning Engineer - Computer Vision

Responsibilities

• From Research to Reality: You'll be the bridge between cutting-edge academic research (activity recognition, multi-camera tracking, Video Language Models) and deployable, production-grade features on https://deeplabel.app .
• Building Solutions: Design, develop, and optimize Deep Learning models for human activity analysis in videos, from initial concept to final deployment.
• System Ownership: Take charge of your modules, ensuring they're robust, efficient, and seamlessly integrated with our AI platform, collaborating closely with our full-stack team.
  

Requirements

• 4-5 years of industry experience, with 2-3 years specifically in practical, project-driven Deep Learning in the Video AI domain.
• Rock-solid Python coding skills.
• Deep practical knowledge of PyTorch and ONNX.
• Proven track record of deploying data pipelines for Computer Vision projects.
• The ability to independently set up, troubleshoot, and optimize Linux workstations (CUDA, OpenCV).
• A strong grasp of Deep Learning concepts (optimizers, attention, masking, model tuning).
• Demonstrated experience with activity detection or object detection implementations.
• A keen ability to read and implement new approaches from research papers.
  

Your Personality Is Just As Important

• You're incredibly curious and love to experiment.
• You have an unwavering commitment to learning and overcoming challenges.
• You're a great communicator and thrive in a collaborative environment.
• You take full ownership of your work, seeing it through to successful deployment.