generalrobotics - Robotics Engineer - Singapore
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Requirements
• Master’s degree (completed or in progress) in Robotics, Computer Science, or a related technical field, or equivalent practical experience. • Current and ongoing work authorization in the country of employment. • 2+ years of experience in the development and implementation of robotics, machine learning, or control algorithms. • Strong proficiency in robotics hardware/software stacks (e.g., ROS/ROS2) and programming languages (e.g., Python, C++). • Demonstrated experience implementing and evaluating end-to-end robot learning systems. • Ability to travel to customer sites as needed. • Proven track record of building and deploying controllers, data acquisition pipelines, and machine learning or classical robotics algorithms on multiple robotic platforms. • Experience utilizing constrained edge compute devices (e.g., NVIDIA Jetson) for data acquisition and model inference. • Experience handling sensitive data and adhering to strict security protocols.
Responsibilities
• System Integration: Independently set up robots for real-world deployments, including integrated edge compute and sensor suites. • Model Deployment: Deploy state-of-the-art AI models and techniques on physical hardware; lead field deployment and evaluation efforts. • Experimental Design: Design, execute, and analyze experiments with rigorous, well-defined hypotheses. • Data Engineering: Design data collection routines to acquire high-quality data from field tests for model fine-tuning. • Technical Literacy: Maintain a deep understanding of model architectures and their effects on real-world performance, specifically regarding computer vision and machine learning from a robotics perspective. • Systems Optimization: Account for common systems constraints—such as bandwidth, compute, and latency—when making modeling choices. Identify and implement optimization opportunities to improve performance on edge compute devices. • Cross-functional Collaboration: Work closely with AI and Simulation Engineers to transition new techniques to the field; communicate critical insights and metrics from real-world testing. • Platform Growth: Translate field-tested patterns and learnings into scalable, streamlined capabilities within the GRID platform.
Benefits
• The typical base pay range for this role is 82000 SGD - 220000 SGD. Your actual pay will be based on factors such as skills and experience.
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