Pay
In line with similar jobs
$173K–$253K against $166K–$240K, the middle half of what similar US postings state.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Matterport - Senior ML Ops Engineer
Sunnyvale, CA, US
Open 6 months, first seen by us 182 days ago- Pay
$173,000–253,000/year · Base — pay source
Pay Transparency: This position offers an annual base salary pay range from $173,000 - 253,000 determined by relevant skills and experience, in addition to uncapped commission opportunities and a generous benefits plan. #LI-PM3 #Matterport
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingAs 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.
This position is located in Sunnyvale, CA and offers a schedule of 4 days on-site and 1 day work from home.
Profile ML models to find performance bottlenecks
Apply quantization, pruning, and distillation to speed up inference
Build CI/CD pipelines for optimized models
Build libraries for running models efficiently on GPUs, CPUs, and edge devices
Design experiments to measure optimization impact on performance and accuracy
From the employer’s posting
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.
This position is located in Sunnyvale, CA and offers a schedule of 4 days on-site and 1 day work from home.
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
build robust continuous integration/continuous deployment (CI/CD) pipelines for optimized models.
Develop and integrate specialized libraries and tools for efficient model execution on various hardware platforms (e.g., GPUs, CPUs, edge devices).
Design and conduct experiments to measure the impact of optimization techniques on model performance and accuracy.
Education & alternatives
Basic Qualifications: * 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. Preferred Qualifications:
Preferred Qualifications: * 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. Perks & Benefits:
About CoStar
Matterport is leading the digital transformation of the built world.
In the employer’s words · Read in context
Posting record
Report an errorOpen 6 monthsWe first saw this posting 182 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- May 5, 2026182 days ago
- Recorded sightings
- 389
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 182
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,331 similar postings that came down. Coming down is not always a hire.
CoStar is hiring
25 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- Azure
- Docker
- GCP
- Kubernetes
- Airflow
- PyTorch
- TensorFlow
Where the posting names them
Basic Qualifications: * 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. Preferred Qualifications:
Preferred Qualifications: * 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. Perks & Benefits:
Your next step
Complete your application on costar.eightfold.ai. The employer’s form will show what is required.
Applying through Eightfold
- You sign in, with Microsoft, LinkedIn, Google, Facebook or a new account, before the application opens.
Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Matterport - Senior ML Ops Engineer
Job Description
CoStar Group is a leading global provider of commercial and residential real estate information, analytics, and online marketplaces. Included in the S&P 500 Index, 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. About Matterport: 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. About the Role: 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. This position is located in Sunnyvale, CA and offers a schedule of 4 days on-site and 1 day work from home. What you will do: * 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. Basic Qualifications: * 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. Preferred Qualifications: * 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. Perks & Benefits: When you join CoStar Group, you’ll experience a collaborative and innovative culture working alongside the best and brightest to empower our people and customers to succeed. We offer you generous compensation and performance-based incentives. CoStar Group also invests in your professional and academic growth with internal training and tuition reimbursement. Our benefits package includes (but is not limited to): * 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 Employee Resource Groups * Complimentary in office gourmet coffee, tea, hot chocolate, fresh fruit, and other healthy snacks Pay Transparency: This position offers an annual base salary pay range from $173,000 - 253,000 determined by relevant skills and experience, in addition to uncapped commission opportunities and a generous benefits plan. #LI-PM3 #Matterport
CoStar Group is an Equal Employment Opportunity Employer; we maintain a drug-free workplace and perform pre-employment substance abuse testing
Job Description
CoStar Group is a leading global provider of commercial and residential real estate information, analytics, and online marketplaces. Included in the S&P 500 Index, 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. About Matterport: 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. About the Role: 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. This position is located in Sunnyvale, CA and offers a schedule of 4 days on-site and 1 day work from home. What you will do: * 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. Basic Qualifications: * 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. Preferred Qualifications: * 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. Perks & Benefits: When you join CoStar Group, you’ll experience a collaborative and innovative culture working alongside the best and brightest to empower our people and customers to succeed. We offer you generous compensation and performance-based incentives. CoStar Group also invests in your professional and academic growth with internal training and tuition reimbursement. Our benefits package includes (but is not limited to): * 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 Employee Resource Groups * Complimentary in office gourmet coffee, tea, hot chocolate, fresh fruit, and other healthy snacks Pay Transparency: This position offers an annual base salary pay range from $173,000 - 253,000 determined by relevant skills and experience, in addition to uncapped commission opportunities and a generous benefits plan. #LI-PM3 #Matterport
CoStar Group is an Equal Employment Opportunity Employer; we maintain a drug-free workplace and perform pre-employment substance abuse testing
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Pay Transparency: This position offers an annual base salary pay range from $173,000 - 253,000 determined by relevant skills and experience, in addition to uncapped commission opportunities and a generous benefits plan. #LI-PM3 #Matterport
- Location & working pattern
Sunnyvale, CA, US
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. This position is located in Sunnyvale, CA and offers a schedule of 4 days on-site and 1 day work from home. What you will do:
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.