Who We Are Sauron protects your family and home, bringing the innovations of autonomous robots and self-driving cars to residential security. Our team is led by veteran entrepreneurs and roboticists, alumni of Zipline, Tesla, and Cloud Kitchens. Sauron has raised an $18M seed round led by A* and Atomic with participation from other leading venture capital firms and angel investors, including 8VC and Flock Safety CEO Garret Langley. The Role | Perception Engineer, Facial Recognition We Value Collaboration, pair programming, and teamwork. Making small improvements and shipping code to production continuously. Taking ownership across the stack. Test-driven development, and refactoring regularly to keep our codebases healthy. You Will Contribute By Leading development efforts on facial recognition systems. Extracting the maximum value from our sensors, fusing all observations available while being robust to occlusions, poor lighting and disguises Leading the collection, labeling, and management of datasets to train and evaluate ML models for facial recognition. Leveraging state of the art models for facial recognition and pushing them to the limits of their performance in this problem domain. Performing trade studies to understand the value of new sensors or processing approaches to system reliability. Analyzing the performance of systems both in simulation and using data from deployments in the field to find headroom and devise solutions to reduce it. Probing the inner workings of neural networks to uncover and mitigate edge case failures. Designing systems that can understand and communicate when they are not working well. Contributing to machine learning infrastructure (e.g. distributed training, continuous model integration, data management, and evaluation of production systems). Your Background Includes 5+ years of professional experience with machine learning for hardware products in a safety-critical field, e.g. aerospace, robotics, medical devices, autonomous vehicles. Passionate about ML, both robust engineering and research challenges. A deep understanding of the theory and practice of modern machine learning techniques. A clear grasp of basic linear algebra, optimization, statistics, and algorithms. Experienced at all facets of training and using deep-learning models, including writing custom layers/operations, optimizing networks for inference on edge compute, reproducibility and evaluation. Extensive experience working with Pytorch, Tensorflow or other modern deep learning frameworks. Familiar with the use of VLMs and other multi-modal models for semantic scene understanding and description. Able to solve complex problems with little supervision. Excellent communicator, both written and verbal. A generalist mindset and can dive in wherever the bottlenecks are, whether that be spooling up cloud compute services to optimizing for embedded systems. #J-18808-Ljbffr Sauron Industries, Inc.
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