CVPR 2026 Career Opportunities

Sunnyvale, CA

About the Role As a Lead Data Annotation Business Analyst at Matterport, a part of CoStar Group, you will be pivotal in building the foundation for our AI and computer vision models. This is a strategic role that goes far beyond traditional business analysis—you will manage the entire lifecycle of data annotation projects, ensuring that our models are trained on high-quality, well-structured datasets that reflect real-world complexity.

You will collaborate with product managers and ML engineers to define ontology requirements, design annotation workflows, and manage internal and external annotation teams. From sampling data and creating annotation guidelines to reviewing outputs and integrating results into production pipelines, you will be the driving force behind the quality and scalability of our training data.

This role offers significant development potential: you will influence Matterport’s data strategy and have the opportunity to evolve into a leadership position overseeing global data operations and annotation strategy.

What You Will Do - Own the Data Annotation Lifecycle: Manage all internal and third-party annotation projects, from requirements gathering to final data delivery. - Define Ontologies and Standards: Work with product and engineering teams to translate model requirements into clear, scalable annotation schemas. - Design and Launch Annotation Projects: Sample datasets, create detailed guidelines, and ensure annotation quality through robust QA processes. - Vendor and Team Management: Coordinate with external providers and internal teams to ensure timely, accurate, and cost-effective project execution. - Integrate and Validate Outputs: Collaborate with ML engineers to ingest annotated data, review results, and iterate for continuous improvement. - Optimize Processes: Develop workflows, tools, and best practices for annotation at scale, leveraging automation where possible. - Drive Strategic Impact: Influence Matterport’s data strategy and contribute to building world-class AI models for spatial computing.

Basic Qualifications - Bachelor's degree required from an accredited, not-for-profit, in-person college/university - A track record of commitment to prior employers. - 3+ years of experience in data operations, annotation management, or business analysis in a technical environment. - Strong understanding of data structures, ontologies, and annotation workflows. - Excellent organizational and project management skills with attention to detail. - Familiarity with ML concepts and data requirements for model training. - Experience working with external vendors and managing cross-functional teams. - Proficiency in tools like Excel, SQL, and project management platforms.

Preferred Qualifications - Experience in computer vision or ML-driven products. - Knowledge of annotation tools and platforms (e.g., Dataloop, Hasty, Scale.ai, Deeplake). - Familiarity with workflow orchestration and automation tools. - Strong analytical skills and ability to translate technical requirements into operational plans. - Demonstrated ability to scale processes and manage multiple projects simultaneously.

Irvine, CA

About the Role: Matterport is looking for a Senior Technical Business Analyst to join our Business Services team.  You’ll be working in a middleware layer that connects our Matterport Platform to multiple systems both internal to Matterport and throughout CoStar Group. The primary focus of this group is to manage integrations at scale, focused on financial and sales backend systems and how they interact with our Platform.  In addition to typical Technical Product Manager responsibilities, this role will play a key part in managing and optimizing our SaaS subscription offerings. You will work closely with Customer Support and Finance teams to ensure seamless onboarding, billing, and ongoing customer satisfaction. Your work will directly impact the customer experience and financial operations, requiring strong communication and problem-solving skills across departments. We handle billions of requests each month, so you must be comfortable optimizing for scale and quality.  The ideal candidate for this role will thrive in a fast-paced environment, be able to pivot when needed and have exceptional personal drive.  You should be able to efficiently build business cases, prioritize work, refine requirements for the engineering team and communicate with stakeholders to achieve optimal outcomes for the business.

This position is in Irvine, CA and offers a schedule of Monday to Thursday in the office and work from home on Fridays.

Responsibilities: - Guide the design, implementation and deployment of new features and services - Collaborate with Customer Support to resolve subscription-related issues and improve customer experience. - Partner with Finance to streamline billing, invoicing, and revenue recognition for SaaS products. - Oversee the end-to-end lifecycle of SaaS subscriptions, including onboarding, renewals, and cancellations. - Work with a cross-functional team of product managers, designers, engineers and QA with direct communication channels - Be an advocate for good engineering practices - Contribute to a learning culture - Generate complete user stories for the development team to efficiently do their work - Respond and assist with issues that are raised by internal and external groups - Holding regular stakeholder/grooming meetings to keep all interested parties updated in project progress - Document user requirements and business rules to be used in application development

Basic Qualifications: - Bachelor's degree required from an accredited, not-for-profit, in-person college/university - A track record of commitment to prior employers - 5+ years of experience as Product Manager, Owner, or Business Analyst - Significant experience designing and delivering features and services in a cloud environment, using a modern OOP language and tooling - Experience with CRM and ERP systems, such as Salesforce and NetSuite ​
- Experience defining and working with order-to-cash processes - Experience and leadership in fast-paced, Agile Scrum environments - Strong project management skills - Experience with technical documentation or product use case writing ​ - Strong experience collaborating with cross-functional teams to achieve business outcomes - Strong written and verbal communication skills; Must be able to communicate at a level appropriate to the audience (stakeholders, peers and senior management)
- Ability to identify opportunities for the team to improve and implement changes as needed - Deep experience with agile frameworks, such as Scrum, Kanban or SAFe

Sunnyvale, CA

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.

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.

Location New York City

Description About Ideogram Ideogram’s mission is to make world-class design accessible to everyone, multiplying human creativity. We build proprietary generative media models and AI native creative workflows, tackling unsolved challenges in graphic design. Our team includes builders with a track record of technology breakthroughs including early research in Diffusion Models, Google’s Imagen, and Imagen Video. We care about design, taste, and craft as much as research and engineering – shipping experiences that creatives actually love.

We’ve raised nearly $100M, led by Andreessen Horowitz and Index Ventures. Headquartered in Toronto with a growing team in NYC, we're scaling fast, aiming to triple over the next year. We're a flat team with a culture of high ownership, collaboration, and mentorship.

Explore Ideogram 3.0, Character and Custom Models blog posts, and try Ideogram at ideogram.ai.

The Opportunity In this role, you will develop the post-training pipeline for our text-to-image foundation models end to end, from data strategy to deployment, advancing techniques such as RLHF, RLAIF, and work on personalization/customization. You will contribute to post-training research that drives measurable gains, and implement and maintain high-throughput fine-tune/eval pipelines. You'll work with a creative and ambitious team of engineers and researchers who are building the future of the creative economy.

What We're Looking For 5+ years of experience in developing machine learning models in JAX, PyTorch, or TensorFlow. Experience in implementing Machine Learning foundations (e.g., Transformer, VAE, Denoising Diffusion models) from scratch. Track record in machine learning innovation and familiarity with Deep Learning and advanced Machine Learning. End-to-end understanding of generative media applications and excitement for pushing the state-of-the-art in generative AI. Ability to debug machine learning models to iteratively improve model quality and performance. Nice to have: Familiarity with kubernetes and docker. Optional: Experience in low-level machine learning optimization, e.g., writing CUDA kernel code.

Sunnyvale, CA

Role Description: We are seeking a Lead Mobile Software Engineer to help lead development for Matterport's 3D technology. We are working with OEM and hardware technology partners to provide cutting-edge capture experiences on next-generation mobile and camera devices.

We are looking for someone who is passionate about building great mobile software and is motivated to take the lead in the creation of mobile apps for capturing, editing, and viewing 3D spaces and objects.

Responsibilities: - Collaborate closely with the engineering team and product marketing to define, design, develop, and deliver new exciting features on Matterport’s applications - Continuously explore, evaluate, and incorporate new technology into our products and processes to improve development efficiency - Deliver a quality software solution using the Agile mobile development cycle - Analyze business requirements, provide development estimates, feedback and proper implementation - Develop, maintain, support, troubleshoot, monitor and optimize existing mobile applications - Research and recommend new mobile tools and applications

Basic Qualifications: - Bachelor’s degree in Computer Science, Electrical Engineering or a related field, from an accredited, not-for-profit University or College, or equivalent experience. - A track record of commitment to prior employers. - 5+ years experience in high-performance software development - 3+ experience in Android mobile development experience with deep technical knowledge of mobile frameworks and how to build reactive UI design - Experience working with RESTful web APIs

Locations: Toronto, ON / San Francisco, CA / Pittsburgh, PA / Remote US

You will…

• Conduct fundamental and applied research in neural reconstruction, including:

• 3DGS / NeRF

• Dynamic scene reconstruction

• Feed-forward reconstruction

• Multi-sensor scene representation learning

• Build scalable reconstruction and simulation systems for dynamic urban scenes, including vehicles, background, lighting, and long-range structure.

• Collaborate with simulation engineers to integrate models into large-scale, distributed training and rendering pipelines.

• Publish high-impact research at top conferences (CVPR, ECCV, ICCV, NeurIPS, ICLR, ICRA, SIGGRAPH).

• Mentor junior scientists and interns; foster a culture of scientific rigor and rapid experimentation.

• Stay current with emerging advances in neural rendering, 3D representation learning, differentiable rendering, and scalable reconstruction systems.

Qualifications:

• Demonstrated technical innovation: You have a Ph.D. in Computer Vision, Machine Learning, Robotics, or a related field or equivalent research experience pushing the boundaries of a technical field..

• Strong prototyping and implementation: You have expert-level Python & PyTorch (or JAX) skills; strong software-engineering fundamentals and experience with distributed training.

• Expert domain knowledge: You have built generative or predictive models of the physical world with scale and efficiency in mind for real-world applications

• Team player: You have worked in a close-knit team of researchers and engineers and have strong communication to deliver successful projects.

Bonus:

• Proven ability to translate research into production-quality code and measurable product impact.

• Demonstrated first-author publications in top-tier venues on topics such as:

• 3DGS / NeRF / neural rendering

• 3D / 4D reconstruction

• Generalizable reconstruction

• Geometry-aware or multi-sensor representation learning

• Experience working with camera, LiDAR, maps, and large-scale driving datasets.

• Strong background in graphics, geometry, rendering systems, or simulation.

The US yearly salary range for this role is: $155,000 - $269,000 USD in addition to competitive perks & benefits. Waabi US Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Locations: Toronto, ON

You will…

• Be part of a team of multidisciplinary Engineers and Researchers using an AI-first approach to enable safe self-driving at scale.
• Build reliable and scalable tools and frameworks to support Autonomous Vehicle (AV) development.
• Lead technical and architecture discussions, collaborating with Researchers and Engineers.
• Mentor other software engineers via code reviews, technical design reviews, and sharing general software development best practices.
• Assist in task planning and estimation.

Qualifications:

• MS/PhD or Bachelors degree with a Computer Science, Robotics and/or similar technical field(s) of study.
• 5+ years of industry experience reading and developing production quality software..
• Experience using languages such as Python, Go, C++, or Rust.
• Experience working in a team environment on a common codebase.
• Ability to learn new technologies quickly.
• Open-minded and collaborative team player with willingness to help others.
• Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.

Bonus/nice to have:

• Experience programming in C++ for a real world robotic system.
• Comfortable with Linux/other unix environments.
• Comfortable with Docker.
• Comfortable with git workflows.
• Experience in robotics or machine learning.
• Experience with automated testing.
• Experience working in an Agile/Scrum environment.
• Experience working with internal cross-functional partners/stakeholders when building software frameworks. -Experience in one or more of the following areas: application development, distributed systems, data storage and processing, parallel computing environments, emulation at scale, software performance, optimization, and profiling, concurrency and determinism, test-driven and API-driven development methodologies, system design/architecture, algorithms, data structure design, and low level threading. Front-end development and tools.

USA, California, Santa Clara

At NVIDIA, we are seeking exceptional engineers to join our autonomous driving team to design, implement, and deploy cutting-edge end-to-end autonomous driving systems, running on NVIDIA chips in mass-production vehicles. Our strategy has evolved from AI 1.0 — building a driver from scratch — to AI 2.0 — teaching an intelligent agent to drive. This next phase leverages LLMs, VLMs, and VLAs to bring unprecedented reasoning, planning capabilities, and interactivity with the driving system to autonomous vehicles and general robotics. Let’s build the future of autonomy—together!

What You’ll Be Doing: - Design and train innovative large-scale models—including generative, imitation, and reinforcement learning—to improve the planning and reasoning capabilities of our driving systems. - Build, pre-train, and fine-tune LLM/VLM/VLA systems for deployment in real-world autonomous driving and robotics applications. - Explore novel data generation and collection strategies to improve diversity and quality of training datasets. - Collaborate with cross-functional teams to deploy AI models in production environments, ensuring performance, safety, and reliability standards are met. - Integrate machine learning models directly with vehicle firmware to deliver production-quality, safety-critical software.

What We Need to See: - Hands-on experience building LLMs, VLMs, or VLAs from scratch or a proven track record as a top-tier coder passionate about autonomous systems. - Deep understanding of modern deep learning architectures and optimization techniques. - Proven record of deploying production-grade ML models for self-driving, robotics, or related fields at scale. - Strong programming skills in Python and proficiency with major deep learning frameworks. - Familiarity with C++ for model deployment and integration in safety-critical systems. - PhD with 4+ years, MS (or equivalent experience) with 6+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.

Ways to Stand Out from the Crowd: - Experience with LLM/VLM/VLA systems deployable to autonomous vehicles or general robotics. - Publications, open-source contributions, or competition wins related to LLM/VLM/VLA systems. - Deep understanding of behavior and motion planning in real-world AV applications. - Experience building and training large-scale datasets and models. - Proven ability to optimize algorithms for real-time performance in resource-constrained environments and strong track record of taking projects from concept to production deployment.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Remote (US based)

About the Role: As a Lead Machine Learning R&D Engineer at Matterport, a part of CoStar Group, you will be at the forefront of innovating and advancing our spatial computing platform. You will play a critical role in researching, designing, and implementing cutting-edge machine learning algorithms and models that enhance our ability to digitize the built world, transform physical spaces into rich digital twins, extract valuable insights from them, and create delightful user experiences that make it easy for our customers to modify and interact with their digital twins. This role requires a deep understanding of ML principles, a passion for solving complex real-world problems in 3D data, computer vision, and a desire to contribute to a product that is revolutionizing how people interact with and understand real estate. You will work within a dynamic R&D environment, collaborating closely with fellow engineers, researchers, and product teams to translate groundbreaking ideas into tangible features that empower our users and expand the capabilities of our platform.

Responsibilities: - Conduct cutting-edge research in machine learning, computer vision, and 3D data processing to develop novel algorithms and models for spatial understanding and digital twin creation. - Design, implement, and optimize robust and scalable ML systems and pipelines for processing large-scale 3D datasets, including point clouds, meshes, and images. - Translate research prototypes into production-ready solutions, collaborating closely with engineering teams to integrate ML models into Matterport's core platform. - Evaluate and benchmark model performance, identify areas for improvement, and drive iterative enhancements to our ML capabilities. - Stay up-to-date with the latest advancements in ML research and industry trends, and proactively identify opportunities to apply new techniques to Matterport's challenges. - Collaborate with cross-functional teams including product managers, software engineers, and other researchers to define project requirements, explore technical feasibility, and deliver high-impact features. - Present research findings and technical solutions to internal teams and potentially the broader ML community. - Contribute to the architectural design and strategic roadmap of Matterport's ML systems and research initiatives. - Contribute to the intellectual property of Matterport through patents and publications.

Basic Qualifications: - Bachelor’s Degree required from an accredited, not for profit university or college.
- A track record of commitment to prior employers - 3+ years of experience in machine learning research and development, with a strong focus on computer vision, 3D data processing, or related areas. - Proficiency in Pytorch and strong programming skills in Python. - Solid understanding of machine learning fundamentals, including deep learning architectures (e.g., CNNs, Transformers), optimization techniques, and evaluation methodologies. - Experience with data manipulation and analysis libraries (e.g., NumPy, Pandas). -Demonstrated ability to conduct independent research, propose novel solutions, and implement them effectively. - Excellent problem-solving skills and the ability to work with complex, real-world datasets. - Strong verbal and written communication skills.

Preferred Qualifications & Skills: - Ph.D. or Masters Degree in Computer Science, Computer Vision, Machine Learning, Robotics, or a related quantitative field. - 5+ years of industry experience in applied machine learning research and development, particularly with shipping models to production. - Demonstrated expertise in one or more of the following areas: neural rendering (e.g., Gaussian splatting, NeRFs, large reconstruction models, world models), 3D computer vision (e.g., SLAM, 3D reconstruction, point cloud processing, mesh processing), image/video generation models, 2D/3D semantic understanding, depth estimation.

Locations: Toronto, ON / San Francisco, CA / Pittsburgh, PA / Remote US

You will…

• Conduct fundamental and applied research in generative and predictive world-modeling

• Video generation and prediction.

• Latent diffusion / autoregressive / flow-matching models.

• Multimodal foundation models for driving scenes.

• LLM / VLM / VLA methods for scene understanding, reasoning, and control.

• Generative scenario modeling and controllable simulation.

• Model distillation.

• Collaborate with engineers to integrate models into large-scale, distributed training and rendering pipelines.

• Publish high-impact research at top conferences (CVPR, ECCV, ICCV, NeurIPS, ICLR, ICRA, SIGGRAPH).

• Mentor junior scientists and interns; foster a culture of scientific rigor and rapid experimentation.

• Stay on top of emerging advances in generative AI, differentiable rendering, knowledge distillation/compression, and robotics.

Qualifications:

• Demonstrated technical innovation: You have a Ph.D. in Computer Vision, Machine Learning, Robotics, or a related field or equivalent research experience pushing the boundaries of a technical field..

• Strong prototyping and implementation: You have expert-level Python & PyTorch (or JAX) skills; strong software-engineering fundamentals and experience with distributed training.

• Expert domain knowledge: You have built generative or predictive models of the physical world with scale and efficiency in mind for real-world applications

• Team player: You have worked in a close-knit team of researchers and engineers and have strong communication to deliver successful projects.

Bonus:

• Proven ability to translate research into production-quality code and measurable product impact.

• Demonstrated publications (first-author) in top-tier venues on topics such as world models, generative simulation, video prediction, diffusion, flow-matching, or foundation models for autonomy.

The US yearly salary range for this role is: $155,000 - $269,000 USD in addition to competitive perks & benefits. Waabi US Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.