Research engineer, SOLA, Geo Map The World

Requirements:

• Bachelor's degree or equivalent practical experience.
• 2 years of experience in machine learning and computer vision.
• Experience in programming with Python.
• Experience in Supervised Machine Learning

Nice to haves:

• PhD in Computer Science, ML/AI, Robotics, or a related field, or equivalent practical experience.
• Experience designing and training Deep Learning (DL) models beyond high-level frameworks, specifically with Transformers, tokenizers, attention mechanisms.
• Experience designing multi-modal, self-supervised pre-training tasks (e.g., contrastive learning, masked autoencoders) to improve data efficiency and manage sparse signals.
• Experience in software engineering with a proficiency in Python or C++, with the ability to build scalable data pipelines.
• Experience cleaning complex, real-world sensor datasets (e.g. handling biases, noise, asynchronous signals).

What you'll be doing:

• Research, design, implement, train, and evaluate large-scale deep learning models for spatial understanding, focusing on multimodal sensor fusion.
• Develop and apply state-of-the-art techniques: transformers, graph neural networks, self-supervised learning, and generative AI.
• Develop novel attention mechanisms to fuse asynchronous data, integrating months-old satellite imagery with real-time vehicle sensor observations (VSO).
• Implement scalable self-supervised and contrastive learning tasks to drive label-efficient learning and automated anomaly detection. Analyze and preprocess large, complex, real-world sensor datasets (e.g., imagery, lidar, navigation traces), including identifying and mitigating biases.
• Collaborate with other engineers and researchers to integrate models into Google Maps' production systems. Contribute to the team's research directions and a culture of innovation. Communicate findings and results to technical and non-technical audiences.

Perks and benefits:

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