Senior Neural Rendering Software Engineer

About Applied Intuition Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co . We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. About the role We are seeking a senior-level engineer with strong foundations in modern real-time rendering systems, neural graphics (e.g., 3D Gaussian-based representations), and high-performance multi-threaded C++/CUDA pipelines. This role sits at the intersection of classical graphics engines and neural rendering systems, with a focus on scaling performance across CPU and GPU for large, real-time simulation workloads. At Applied Intuition, engineers are expected to take ownership of technically complex systems, make architecture-level decisions, work closely with internal and external users, and help evolve both the product and the engineering culture. At Applied Intuition, you will: Own end-to-end development and optimization of neural rendering systems, including 3D Gaussian-based representations and other learned scene representations, across multiple products and sensor modalities Design and scale GPU pipelines using CUDA for neural scene training, inference, and real-time rasterization — including data layout, memory movement, synchronization, and kernel performance Architect and optimize multi-threaded C++ systems for scene management, streaming, scheduling, and CPU-side orchestration of neural and hybrid rendering workloads Research, prototype, and productionize state-of-the-art neural rendering and reconstruction techniques, keeping the engine at the frontier of the field Integrate neural rendering outputs with existing simulation and rendering infrastructure, including lightweight physically-based rendering (PBR) components where classical techniques complement neural approaches Build internal tooling and automated benchmarking and profiling infrastructure, including CI-based performance regression tracking for neural pipelines We're looking for someone who has: 4+ years of industry or research experience in neural rendering, neural 3D simulation, or closely related fields (graphics, vision, or performance-critical GPU systems) A minimum of a Bachelor's degree in computer science, computer engineering, or equivalent Hands-on experience with neural scene simulation such as 3D Gaussian splatting, NeRFs, neural radiance fields, or similar learned volumetric/surface representations Strong GPU programming skills, including CUDA and/or shader development, with an understanding of CPU–GPU coordination for training and inference workloads Strong experience optimizing multi-threaded C++ applications, including task systems, synchronization, memory ownership, and cache behavior Strong intuition for performance debugging, profiling, and system-level optimization across CPU and GPU Nice to have: Publications or significant project contributions in neural rendering, novel view synthesis, or 3D reconstruction Experience productionizing research-grade neural graphics systems into real-time engines Familiarity with differentiable rendering or differentiable simulation frameworks Experience designing or optimizing real-time ray tracing systems Familiarity with autonomy-related sensors (cameras, LiDAR, radar, ultrasonic) and their simulation or rendering requirements Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment. Applied Intui