Research Engineer
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Requirements
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. • Research experience in machine learning, robotics, and natural language processing. • Experience with developing robotics algorithms or machine learning models at scale. • Programming experience in Python/C++. Good understanding of deep learning frameworks like Pytorch or Jax. • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment. • Master's/PhD in Robotics, Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. • Direct experience in robotics, computer vision, or machine learning research. Experience with the Transformer model architecture. • First author publications at peer-reviewed AI and robotics conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICRA, IROS). • Experience with high fidelity simulation platforms such as AirSim, CARLA, Isaac Sim among others. • Experience building efficient robotics pipelines involving sensor fusion and model inference • Good understanding of systems considerations and the ability to factor these into model choices.
Responsibilities
• Design methods, tools, and infrastructure to push forward the state of the art in robotics and foundation models. • Define research goals informed by practical engineering concerns. • Adapt standard machine learning models and frameworks to robotics applications (e.g. computer vision, SLAM, navigation). • Work with high fidelity simulation platforms for synthetic data generation. • Design data loading and training pipelines for large scale foundation model training. • Contribute to experiments, including designing experimental details, writing reusable code, running model evaluations, and organizing results. • Contribute to publications and open-sourcing efforts.
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.