Matterport - Senior ML Ops Engineer

CoStar-posted 4 months ago
$173,000 - $213,000/Yr
Full-time • Senior
Sunnyvale, CA
5,001-10,000 employees
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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., TensorFlow, PyTorch) and optimization libraries.
  • Solid understanding of machine learning algorithms, model architectures, and deep learning concepts.
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) and deploying ML models in cloud environments.
  • Familiarity with version control systems (e.g., Git) and agile development methodologies.
  • Excellent problem-solving skills and attention to detail, particularly in model performance and accuracy.
  • Strong verbal and written communication skills.
  • Master's degree in Computer Science, Data Science, or a related quantitative field.
  • 5+ years of industry experience in ML Model Optimization, ML Engineering, or MLOps, particularly with large-scale 2D/3D computer vision models.
  • Experience with hardware-aware model optimization and deployment to edge devices.
  • Knowledge of model compression techniques and their practical application.
  • Experience with workflow orchestration tools (e.g. Temporal, Airflow, Kubeflow).
  • Familiarity with containerization technologies (e.g., Docker, Kubernetes).
  • Demonstrated ability to build and maintain robust, scalable, and automated ML model deployment pipelines.
  • Experience working in a fast-paced R&D environment.
  • Excellent communication skills, both written and verbal, with the ability to articulate complex technical concepts to diverse audiences.
  • Comprehensive healthcare coverage: Medical / Vision / Dental / Prescription Drug
  • Life, legal, and supplementary insurance
  • Virtual and in person mental health counseling services for individuals and family
  • Commuter and parking benefits
  • 401(K) retirement plan with matching contributions
  • Employee stock purchase plan
  • Paid time off
  • Tuition reimbursement
  • Access to CoStar Group’s Culture Employee Resource Groups
  • Complimentary in office gourmet coffee, tea, hot chocolate, fresh fruit, and other healthy snacks
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