Augmodo is at the forefront of spatial computing, where mapping connects the digital and physical worlds. As a ML Infrastructure Engineer, you will play a key role in our computer vision and infrastructure teams to develop large-scale, real time systems and pipelines handling petabytes of video, image and analytics data. You will partner with both cloud and edge/store engineers to scale and optimize ML CI/CD development for ultimately tens of thousands of stores worldwide. - Build real-time, scalable and reliable video and image processing systems and pipelines - Develop and manage petabyte-scale data infrastructure and systems - Design and develop APIs to automate ML development lifecycle from training, testing to deployment - Identify and optimize system performance, including for ML inference and deployment on both cloud and real-time edge systems. - Expertise in large scale, real-time data pipelines, infrastructure and distributed systems - Strong programming skills in Python and one of Java/Scala/Go/Rust/C++. - Excellent problem-solving and analytical skills. - Strong communication and teamwork skills. - 5 years of experience in production-grade ML systems and data pipelines - Bachelor in Computer Science, Robotics, or a related field. - Master's degree or PhD in Computer Science or a related technical field - Familiarity with machine learning frameworks (e.g., PyTorch, TensorFlow) and computer vision libraries (e.g., OpenCV). - Experience in large scale Computer Vision and deep-learning ML development $155,000 - $210,000 USD + Equity