AI Engineer

An innovative early-stage AI startup is redefining how humans interact with the digital world through cutting-edge Computer Vision technology.

The company develops advanced software-based sensing solutions that leverage standard built-in cameras to enable seamless, intuitive user experiences.

Operating at the forefront of Applied AI, the organization offers a high-impact environment where researchers drive the entire lifecycle from state-of-the-art (SOTA) research to full-scale production.

Role Overview:

• Full-Cycle Research: Leading the research and development of advanced algorithms in Computer Vision and Deep Learning, from initial conceptualization to deployment.
• Algorithmic Innovation: Implementing SOTA methods in Object Detection, Multi-object Tracking, and Instance Segmentation.
• Visual Data Processing: Developing sophisticated Image and Video Processing pipelines to extract real-time insights from visual streams.
• 3D & Spatial Analysis: Working on complex spatial computing challenges, including 3D modeling and geometric transformations.
• Production-Grade AI: Bridging the gap between academic research and real-world performance using Python, C++, and modern DL frameworks.
• Collaborative R&D: Working within an elite team of scientists and engineers to push the boundaries of human-computer interaction.

Requirements:

• 5+ years of professional industry experience in AI/Computer Vision – Mandatory.
• Deep hands-on experience with Deep Learning (DL) frameworks and architectures – Mandatory.
• Proven track record in Computer Vision (CV) research and implementation – Mandatory.
• Expert-level proficiency in Python – Mandatory.
• Experience with C++ and performance optimization – Significant Advantage.
• Solid background in Object Detection, Tracking, or Segmentation – Mandatory.
• Familiarity with TensorFlow, Keras, or PyTorch in production environments.
• Strong mathematical foundation, particularly in linear algebra and 3D geometry.
• Ability to work independently and lead complex research projects in a fast-paced startup setting.