Research Scientist, Neural Rendering, Google Beam

About the job

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

The Google Beam team drives world-leading algorithms and system research to power immersive Google Beam telepresence experiences. We develop AI models that synthesize photorealistic 3D views from camera inputs in real time. Our work spans the full research and engineering stack. We focus on reducing hardware complexity, lowering bandwidth requirements, improving robustness, and pushing visual quality enabling Beam products to deliver breakthrough communication experiences that make people feel like they are truly together. Through deep research and rapid prototyping, we de-risk future product directions and build the AI foundations for scalable, accessible 3D telepresence.

Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Define and drive research directions in AI and computer vision that push the boundaries of real-time 3D telepresence.
• Formulate novel approaches to open problems, translating fundamental research insights into transformative product experiences.
• Collaborate with cross-functional teams across hardware, software, and product to shape the technical direction and roadmap.
• Conduct rigorous experiments to validate hypotheses, de-risk new technical directions, and inform strategic decisions through prototypes and data-driven evaluations.
• Publish and present research and represent Google in the broader research community.

Qualifications

Minimum qualifications:

• PhD in Computer Science, or a related field, with a focus on computer vision, machine learning, or computer graphics, or equivalent practical experience.
• 2 years of experience in Python and deep learning frameworks (e.g., JAX, Flax, Gemma, or Pytorch)
• One or more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, SIGGRAPH etc.).

Preferred qualifications:

• Research experience with track record in one or more of: neural rendering, generative models, 3D reconstruction, video models, or real-time vision systems.
• Experience building real-time AI or computer vision systems with strict latency and performance constraints, especially on edge devices or resource-constrained hardware.
• Experience tech-leading a team, including setting research roadmaps, mentoring researchers, and driving technical decisions.
• Demonstrated ability to break down ambiguous program goals into staged milestones and deliver end-to-end from research concept to shipped product.
• Excellent communication skills, with the ability to articulate complex technical ideas clearly to both technical and non-technical audiences.