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Gaussian Splatting Jobs (NOW HIRING)

Nvidia

OR · On-site

Neural reconstruction and Gaussian Splatting are changing how 3D worlds are collected, represented, optimized, and rendered. These workloads push the limits of GPU computing, differentiable rendering ...

Epitec

Senior Graphics Engineer V

Menlo Park, CA · On-site

$95 - $100/hr

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

Umd

Post-Doctoral Associate

College Park, MD · On-site

$48K - $65K/yr

This postdoc will perform research on 3D scene reconstruction, novel view synthesis and inverse rendering, building on state of the art techniques such as neural radiance fields, Gaussian splatting ...

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How much do gaussian splatting jobs pay per year?

As of Jun 8, 2026, the average yearly pay for gaussian splatting in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a Gaussian Splatting job?

A Gaussian Splatting job typically involves rendering 3D scenes using point-based representations with anisotropic Gaussians. This technique is used in graphics and visualization to efficiently approximate surfaces and lighting effects. Professionals in this role may work on optimizing algorithms, improving rendering quality, or integrating Gaussian splatting into real-time applications like games and simulations. Strong skills in computer graphics, math, and programming are often required.

What are the key skills and qualifications needed to thrive in the Gaussian Splatting position, and why are they important?

To excel as a Gaussian Splatting specialist, candidates typically need a strong background in computer graphics, computational mathematics, and 3D rendering, often supported by an advanced degree in computer science, engineering, or a related field. Familiarity with programming languages such as C++, Python, and specialized graphics libraries (e.g., CUDA, OpenGL, Vulkan), as well as experience with neural rendering frameworks, is commonly required. Creative problem-solving, attention to detail, and strong collaboration skills are key soft attributes in this role. These skills are critical for developing efficient, high-quality neural rendering solutions and for integrating cutting-edge visualization techniques into real-time graphics pipelines.

What are the typical daily tasks of a Gaussian Splatting specialist within a visual computing team?

A Gaussian Splatting specialist typically spends their days designing and implementing algorithms for real-time neural scene rendering, testing rendering performance on various hardware, and troubleshooting graphical artifacts or efficiency bottlenecks. Their work often involves close collaboration with software engineers, 3D artists, and machine learning researchers to optimize the integration of splatting techniques into existing graphics pipelines. Regular responsibilities may also include participating in code reviews, contributing to technical documentation, and staying updated on the latest advancements in 3D rendering technology. This collaborative, dynamic environment offers the opportunity to work on visually impactful projects and influence cutting-edge visualization tools.

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Gaussian Splatting jobs near you

Simulation Engineer

Humble Robotics

San Francisco, CA

Full-time

Posted 18 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. 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.