Matterport - Senior ML Ops Engineer

Matterport - Senior ML Ops Engineer Job Description

CoStar Group (NASDAQ: CSGP) is a leading global provider of commercial and residential real estate information, analytics, and online marketplaces. Included in the S&P 500 Index and the NASDAQ 100, CoStar Group is on a mission to digitize the world’s real estate, empowering all people to discover properties, insights and connections that improve their businesses and lives. We have been living and breathing the world of real estate information and online marketplaces for over 35 years, giving us the perspective to create truly unique and valuable offerings to our customers.

We’ve continually refined, transformed, and perfected our approach to our business, creating a language that has become standard in our industry, for our customers, and even our competitors. We continue that effort today and are always working to improve and drive innovation. This is how we deliver for our customers, our employees, and investors. By equipping the brightest minds with the best resources available, we provide an invaluable edge in real estate.

Matterport is leading the digital transformation of the built world. Our groundbreaking spatial computing platform turns buildings into data making every space more valuable and accessible. Millions of buildings in more than 170 countries have been transformed into immersive Matterport digital twins to improve every part of the building lifecycle from planning, construction, and operations to documentation, appraisal, and marketing.

As a Senior MLOps Engineer at Matterport, a part of CoStar Group, you will be pivotal in enhancing the performance, efficiency, and scalability of our machine learning models. You will be responsible for identifying bottlenecks, applying advanced optimization techniques, and deploying highly efficient models into production. You will work closely with ML R&D Engineers and other engineering teams to analyze model performance, optimize inference speed and resource utilization, and ensure the seamless integration of optimized models into our spatial computing platform.

This role requires a strong understanding of machine learning principles, expertise in model optimization techniques, and a passion for pushing the boundaries of what's possible with efficient ML deployment. You will contribute to a product that is revolutionizing how people interact with and understand real estate by ensuring our models are robust, fast, and deliver exceptional user experiences.

• Analyze and profile machine learning models to identify performance bottlenecks and areas for optimization.
• Implement and apply model optimization techniques such as quantization, pruning, distillation, and neural architecture search to improve inference speed and reduce resource consumption.
• Develop and integrate specialized libraries and tools for efficient model execution on various hardware platforms (e.g., GPUs, CPUs, edge devices).
• Collaborate with ML R&D Engineers to understand model architectures, training procedures, and deployment requirements.
• Design and conduct experiments to measure the impact of optimization techniques on model performance and accuracy.
• Automate model optimization workflows and build robust continuous integration/continuous deployment (CI/CD) pipelines for optimized models.
• Stay up-to-date with the latest research and industry trends in ML model optimization, hardware acceleration, and efficient AI.
• Contribute to the continuous improvement of MLOps practices and infrastructure for model deployment and monitoring.
• Ensure the scalability and reliability of optimized models in production environments.

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience.
• 3+ years of experience in machine learning engineering, with a focus on model optimization and deployment.
• Proficiency in Python and strong programming skills.
• Experience with machine learning frameworks (e.g., Tensor Flow, PyTorch) and optimization libraries.
• Solid understanding of machine learning algorithms, model…