Lead Edge AI Engineer
Job Description
Get to know the Team
The Data Science (Geo Vision) team at Grab focuses on improving the maps and building map-based intelligence such as localization, routing, travel time estimation, and traffic forecasting. We use Computer Vision and conventional machine learning methods on a variety of signals—specifically utilizing edge device footage—to understand our locations and road networks.
Get to know the Role
We are looking for a Lead Data Scientist / Edge AI Engineer to lead edge development for our edge devices. A key focus will be Multi-Task & Action Recognition Development, where the successful candidate will be responsible for developing and refining multi-task learning models and video action recognition systems for our edge devices.
You will work onsite and will report to the Head of Data Science based in the Cluj Office.
The Critical Tasks You Will Perform
• Multi-Task & Action Recognition Development: Develop and refine multi-task learning models (specifically Hydranet architecture) and video action recognition systems using PyTorch.
• Edge Deployment & Engineering: Deploy Computer Vision algorithms into embedded Android platforms, utilizing the Qualcomm SNPE / QNN SDK to interact directly with the DSP.
• Resource Efficiency: Conduct rigorous performance analysis to reduce power consumption and manage thermal constraints. You will ensure model switching latency remains minimal to maintain recording integrity.
• System Stability: Implement safety mechanisms to ensure system stability during dynamic model graph reconfiguration.
• Collaboration: Collaborate with Firmware and Mobile teams to integrate signals for model decision-making.
Requirements
Function: Engineering
Experience Level: Mid-Senior Level