Matterport - Senior ML Ops Engineer

Description

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

Requirements

• Proficiency in Python and strong programming skills.
• 3+ years of experience in machine learning engineering, with a focus on model optimization and deployment.
• Excellent problem-solving skills and attention to detail, particularly in model performance and accuracy.
• Experience with workflow orchestration tools (e.g. Temporal, Airflow, Kubeflow).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and deploying ML models in cloud environments.
• Solid understanding of machine learning algorithms, model architectures, and deep learning concepts.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and optimization libraries.
• Bachelor's degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience.
• Familiarity with version control systems (e.g., Git) and agile development methodologies.
• Familiarity with containerization technologies (e.g., Docker, Kubernetes).
• Demonstrated ability to build and maintain robust, scalable, and automated ML model deployment pipelines.
• Experience with hardware-aware model optimization and deployment to edge devices.
• Strong verbal and written communication skills.
• Knowledge of model compression techniques and their practical application.
• 5+ years of industry experience in ML Model Optimization, ML Engineering, or MLOps, particularly with large-scale 2D/3D computer vision models.
• Excellent communication skills, both written and verbal, with the ability to articulate complex technical concepts to diverse audiences.
• Experience working in a fast-paced R&D environment.
• Master's degree in Computer Science, Data Science, or a related quantitative field.

Benefits

• Complimentary in office gourmet coffee, tea, hot chocolate, fresh fruit, and other healthy snacks
• 401(K) retirement plan with matching contributions
• Comprehensive healthcare coverage: Medical / Vision / Dental / Prescription Drug
• Tuition reimbursement
• Commuter and parking benefits
• Virtual and in person mental health counseling services for individuals and family
• Life, legal, and supplementary insurance
• Employee stock purchase plan
• Paid time off
• Access to CoStar Group’s Culture Employee Resource Groups

Training + Development

Interview process

Visa Sponsorship

Security clearance