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Neural Rendering Jobs in Pleasanton, CA (NOW HIRING)

H R PUNDITS INC

Senior Graphics Engineer

Santa Clara, CA · Remote

$130K/yr

... neural rendering, radiance fields, or Gaussian splatting Experience with advanced rendering techniques such as ray tracing, deferred shading, or HDR Experience working with modern AI tooling ...

LiveX AI Inc.

AI Engineer

Palo Alto, CA · On-site

$150 - $210/hr

Stay current with the latest research in generative video, multimodal AI, and neural rendering, and bring novel techniques into our stack. Qualifications: * 3+ years of hands‑on ML engineering ...

Unitytech

Staff Machine Learning Engineer

Mountain View, CA · On-site

$218K - $327K/yr

The opportunity We are building the next generation of AI-driven game experiences - generative world models, neural rendering, and multi-modal understanding that turn images, text, and 3D primitives ...

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Neural Rendering information

See Pleasanton, CA salary details

$15

$23

$39

How much do neural rendering jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for neural rendering in Pleasanton, CA is $23.48, according to ZipRecruiter salary data. Most workers in this role earn between $19.52 and $23.56 per hour, depending on experience, location, and employer.

What is neural rendering?

Neural rendering is a cutting-edge technique in computer graphics and artificial intelligence that uses neural networks to generate, manipulate, or enhance images and videos, often producing photorealistic or novel visual content. Unlike traditional rendering methods, which rely heavily on physical modeling and computational geometry, neural rendering leverages deep learning algorithms to synthesize visual data from inputs like 3D models, images, or text descriptions. This technology is used in applications such as virtual reality, gaming, special effects, and creating digital avatars. Neural rendering can significantly reduce the computational cost and time needed for high-quality image synthesis, making it a transformative tool in visual computing industries.

What are the key skills and qualifications needed to thrive as a neural rendering engineer, and why are they important?

To thrive as a Neural Rendering Engineer, you need a strong background in computer graphics, deep learning, and mathematics, generally with a degree in computer science, electrical engineering, or a related field. Experience with frameworks like PyTorch or TensorFlow, GPU programming (CUDA), and familiarity with 3D rendering engines is highly valuable. Strong problem-solving skills, creativity, and effective teamwork set exceptional candidates apart in this role. These competencies are crucial for developing innovative rendering solutions that bridge artificial intelligence and visual computing, enabling breakthroughs in graphics technology.

What are some common challenges faced by professionals working in neural rendering, and how can they be addressed?

Professionals in Neural Rendering often encounter challenges related to computational resource demands and the integration of novel algorithms into existing graphics pipelines. Handling large datasets and optimizing neural network architectures for real-time performance can also be complex. Collaboration with cross-functional teams—such as graphics engineers, researchers, and product managers—is essential to ensure solutions are both technically feasible and aligned with project goals. Staying updated with the latest research and leveraging open-source frameworks can help address these challenges effectively.

What is the difference between Neural Rendering vs 3D Graphics Programmer?

AspectNeural Rendering3D Graphics Programmer
Required SkillsMachine learning, neural networks, deep learning frameworksGraphics APIs, shader programming, 3D modeling
Work EnvironmentResearch labs, AI-focused companies, tech startupsGame studios, visual effects companies, simulation firms
Industry UsageEmerging in AI-driven visualization and renderingEstablished in gaming, film, and simulation industries

Neural Rendering focuses on using neural networks and AI techniques to generate or enhance visual content, often requiring expertise in machine learning. In contrast, 3D Graphics Programmers develop traditional graphics algorithms, shaders, and models for real-time rendering. While both roles involve visual content creation, Neural Rendering is more research-oriented and AI-driven, whereas 3D Graphics Programming emphasizes technical implementation within graphics pipelines.

What cities near Pleasanton, CA are hiring for Neural Rendering jobs?

Cities near Pleasanton, CA with the most Neural Rendering job openings:

Neural Rendering jobs near you
Infographic showing various Neural Rendering job openings in Pleasanton, CA as of July 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 76% Physical, 2% Hybrid, and 22% Remote job distribution, with an average salary of $48,843 per year, or $23.5 per hour.

Principal Machine Learning Engineer, Geometric Vision

Wayve

Sunnyvale, CA • On-site

Full-time

Posted 16 days ago

Job description

The role
As a Principal Engineer on the Model Foundations team you will build the geometric vision and 3D foundation models that underpin our autonomous driving systems.You will work at the intersection of large-scale deep learning, geometric computer vision, and real-world robotics, developing models that learn 3D structure and dynamics from fleet-scale sensor data.
You will be a hands-on technical leader. You will set direction for geometric vision, prototype and train new model architectures, build the data and supervision needed to scale them, and take successful ideas through to deployment on real vehicles.
Key responsibilities
  • Design and train 3D foundation models and world models using large-scale driving data.
  • Develop model architectures for 3D perception, geometric reasoning, reconstruction, and world modeling across space and time.
  • Build scalable data generation and auto-labeling pipelines that produce high-quality geometric supervision from large volumes of sensor data.
  • Develop and scale offline SLAM and 3D reconstruction systems and pipelines, using large-scale sensor data to recover accurate trajectories, scene geometry, calibration signals, and geometric supervision for model training and evaluation.
  • Develop and apply techniques in multi-view geometry, neural rendering, NeRFs, Gaussian Splatting, implicit 3D representations, and feedforward 3D modeling.
  • Explore geometry-aware tokenization and representation learning, including efficient ways to encode and fuse information across cameras, viewpoints, time, and sensing modalities.
  • Develop foundation vision models that make effective use of camera, radar, LiDAR, and other sensor data for learning rich representations of the physical world.
  • Explore video and generative modeling approaches for learning scene structure, dynamics, and future evolution from driving data.
  • Train and evaluate models at scale on distributed compute, rapidly iterating on architectures, objectives, data, and training recipes.
  • Develop automated evaluation and ground-truth systems for measuring geometric consistency, reconstruction quality, 3D understanding, and downstream driving performance.
  • Optimize and deploy models into production autonomous-driving systems, working across model architecture, inference, and onboard constraints.
  • Set technical direction for geometric vision at Wayve and work closely with researchers and engineers across foundation models, perception, simulation, data, sensing, and deployment.
About you
In order to set you up for success as a Principal Machine Learning Engineer, Geometric Vision at Wayve, we're looking for the following skills and experience.
Essential
  • Deep expertise in 3D computer vision, geometric vision, or 3D machine learning, with experience in areas such as multi-view geometry, neural rendering, reconstruction, implicit representations, or world modeling.
  • Strong experience designing, training, and evaluating modern deep-learning models at scale, using PyTorch or a comparable framework.
  • Strong mathematical and technical foundations in geometry, linear algebra, probability, optimization, and 3D transformations, combined with excellent software engineering skills in Python and C++
  • A track record of taking difficult research problems from idea to working system, including building large-scale data, training, evaluation, or deployment pipelines.
  • Principal-level technical leadership: the ability to identify high-leverage problems, set research and engineering direction, make strong architectural decisions, and raise the technical bar across teams.

Desirable
  • 3D and geometric vision: multi-view geometry, dense 3D reconstruction, neural fields, NeRFs, Gaussian Splatting, or feedforward 3D models.
  • Foundation and world models: large-scale vision pre-training, self-supervised learning, video models, generative models, or learned scene dynamics.
  • Geometric data engines: offline SLAM, structure-from-motion, reconstruction, calibration, auto-labeling, and large-scale ground-truth generation.
  • Multimodal perception: learned representations and fusion across camera, radar, LiDAR, and other sensing modalities.
  • Production ML systems: distributed training, large-scale experimentation, and deploying neural networks on real-time, resource-constrained hardware.

This is a full-time role based in our office in Sunnyvale. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. The reasonably estimated salary for this role ranges from $ 407,330 to $ 460,020 plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.

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