Research Scientist, Neural Rendering, Beam
This job at a glance
- Who can apply
- 2–4 years of experience
- Must know
- Data structures & algorithmsMachine learningPythonDeep learningPyTorch
- Nice to have
- Computer visionProduct management
- Work
- On-site in Seattle
- Pay
- Not stated by the employer.
- Skill demand
- Python26%Machine learning19%Data structures & algorithms6%Deep learning2%of 98 similar entry-level jobs posted in the US this week
- Listed
- Nov 10, 2026 · still open
Sign in free to see which of these skills your resume already shows.
About the Role
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.
Key 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.
Requirements & Tech Stack
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.