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Neural Rendering Jobs (NOW HIRING)

Humble Robotics

Simulation Engineer

San Francisco, CA · On-site

This work will work heavily with modern neural rendering approaches: Gaussian splatting, world models, and learned sensor models. We're a small team early in the build. You'll have real influence ...

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 ...

Umd

Graphics Software Engineer

College Park, MD · On-site

$138K - $171K/yr

This position requires passion for real-time XR programming on cutting-edge hardware while closely integrating AI/ML for neural rendering, generative medical visualization, real-time inference, and ...

Parallel Domain

Principal Technical Artist

Seattle, WA · On-site +1

$144K - $173K/yr

Gaussian splat scene reconstruction, neural rendering, AI-assisted content workflows, and modern procedural systems are reshaping what a tech artist's day looks like. We're hiring a Principal ...

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Neural Rendering information

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How much do neural rendering jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for neural rendering in the United States is $21.10, according to ZipRecruiter salary data. Most workers in this role earn between $17.55 and $21.15 per hour, depending on experience, location, and employer.

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 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.
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Neural Rendering jobs near you

Simulation Engineer

Humble Robotics

San Francisco, CA • On-site

Full-time

Re-posted 19 days ago

Job description

About Humble Robotics 

Working at Humble Robotics means taking on the biggest change in ground transportation in decades. We’re building an autonomous, zero-emissions hauler that dramatically lowers the cost of freight with groundbreaking vision-based AI, designed for today’s global logistics network.

We’re a fast-moving, close-knit team of AV industry veterans and innovative thinkers. We don’t believe culture can be engineered – but when it falls into place, it’s a once-in-a-lifetime adventure.

Progress has never felt so present.

Position Overview

Open to a range of experience levels

We’re looking for a software engineer to join our simulation team. You’ll build the systems and tools that support closed-loop model testing, synthetic data generation, and sensor simulation. This work will work heavily with modern neural rendering approaches: Gaussian splatting, world models, and learned sensor models.

We’re a small team early in the build. You’ll have real influence over both what we build and how we build it.

Key Responsibilities
  • Build and maintain Python pipelines and tooling for closed-loop testing and synthetic data generation
  • Integrate modern neural rendering techniques into our sensor simulation stack (e.g., Gaussian splatting, NeRFs, world models)
  • Expand and maintain the scenario library and benchmark suite used to evaluate perception, planning, and control
  • Develop synthetic data generation workflows, including scenario and agent behavior generation, to support model training
  • Work closely with ML and autonomy engineers to measure and reduce sim-to-real gaps, ensuring simulation reflects real-world behavior
Minimum Qualifications
  • BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field—or equivalent industry experience
  • Strong proficiency in Python (primary language of the simulation stack)
  • Experience working with simulation systems, ideally in robotics, autonomous vehicles, or other high-fidelity domains
  • Eligible to work in the United States
Preferred Qualifications
  • Experience with neural rendering or generative simulation (e.g., Gaussian splatting, NeRFs, world models, diffusion-based methods)
  • Depth in one or more areas of simulation: closed-loop testing, scenario design, log replay, or sensor simulation
  • Experience building benchmarks or evaluation frameworks used across a team
  • Experience developing synthetic data pipelines that improved downstream model performance
  • Familiarity with real-time robotic systems and their constraints on simulation fidelity
  • Comfortable working on a small team with high ownership and fast iteration cycles
Compensation
This role is eligible for base salary \+ benefits \+ equity compensation. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by additional factors, including qualifications, skills, experience, and location.
Additional Information

As part of the interview process, we may use Artificial Intelligence (AI) tools to compare your qualifications and experience to the job description. A human reviews all AI output and makes a final hiring decision. Humble Robotics does not rely on the output to make any employment decisions. Some applicants may have a legal right to opt-out of the use of AI as part of our interview process. Contact **legal@humblerobotics.ai** to exercise this right or if you have further questions on the use of AI tools in our hiring process.

Humble Robotics is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, marital status or any other characteristics protected by law. Humble Robotics will consider qualified applicants with arrest and conviction records in a manner consistent with local ordinances.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.