GPU Shader Visualization, Senior Software Engineer
Vivodyne
Human data before the clinic
Vivodyne accelerates the successful discovery, design, and development of human therapeutics through the convergence of novel biology, robotics, and AI. Our platform enables customers to massively de-risk drug candidates by testing them against functional, lab-grown, human organs and multi-organ systems. We conduct preclinical discovery and clinical development campaigns to generate new therapeutics and clinical strategies from these proprietary, physiologically-realistic human organ tissues at unprecedented scale, speed, and quality through automation and machine learning. We’re financially backed by some of the most selective and successful venture funds, and several “top 10” global pharmaceutical innovators have already partnered with us to strengthen and speed their therapeutic pipelines.
To learn more visit us at www.vivodyne.com.
Role
We are seeking a GPU Shader Visualization Software Engineer who is passionate about achieving the highest possible 3D visualization performance on high-end NVIDIA discrete GPUs for cutting-edge scientific applications. In this role, you will design and implement high-performance shader pipelines, rendering algorithms, and GPU acceleration strategies to display millions of gigabyte-scale 3D tissue images with multiple overlay annotations in real-time. You will work closely with a cross-functional team of AI researchers, biologists, tissue engineers, and robotics experts to build advanced interactive visualization tools that power Vivodyne’s next-generation platform for drug discovery and tissue engineering.
Responsibilities
- Develop and optimize GPU shader code to achieve maximum rendering performance and visual fidelity on modern NVIDIA GPUs.
- Design and implement rendering pipelines leveraging Vulkan (required) and possibly Metal (a plus), while welcoming outstanding developers experienced in OpenGL looking to transition.
- Build robust, beautiful, and functional 3D visualization UIs, ensuring that complex biological data is presented in clear and intuitive ways.
- Collaborate on hierarchical caching strategies and compression-based progressive loaders to enable real-time access to extremely large imaging datasets.
- Integrate C++ application logic and GPU pipelines on Linux as the primary end-user platform.
- Work alongside software, AI, and biology teams to create fast, interactive overlays for annotations, measurements, and image processing tasks.
- Adhere to engineering best practices, including code reviews, version control, continuous integration, testing, and documentation for GPU-related modules.
- Provide technical leadership in GPU programming and shader optimization, sharing expertise with colleagues and mentoring junior engineers on 3D rendering techniques.
- Collaborate closely with internal and external stakeholders to understand scientific visualization objectives and deliver solutions that exceed user expectations.
- Stay current with the latest graphics technologies, GPU hardware trends, and scientific visualization best practices.
- Assist in troubleshooting performance bottlenecks, diagnosing rendering issues, and ensuring robust error handling and logging.
Requirements and Expectations
Technical Excellence
- Deep understanding of GPU architectures, shading languages, real-time rendering pipelines, and performance profiling tools.
- Expert knowledge of Vulkan or an exceptional track record in OpenGL (with eagerness to transition to Vulkan).
- Familiarity with Metal is desirable but not required.
- Strong fluency in C++ programming, including modern C++ standards and best practices.
- Experience on Linux as the primary development or deployment platform.
- Proven ability to produce high-performance, scalable rendering systems that handle extremely large volumes of data.
Scientific Visualization Mindset
- Passion for rendering complex 3D scientific data—experience with biology or medical imaging is beneficial but not strictly required.
- Experience with hierarchical caching, progressive loading, and compression strategies to handle very large 3D datasets.
- Proven track record of building engaging and intuitive 3D UIs that serve both expert and non-expert users.
Problem Solving
- Demonstrated capacity to profile, optimize, and debug GPU-bound applications.
- Willingness to approach novel rendering challenges from first principles, especially when there are few existing best practices for large-scale tissue imagery.
- Ability to make data-driven decisions and measure performance gains in real-world scenarios.
Orchestration and Teamwork
- Ability to collaborate with cross-functional teams (AI scientists, software engineers, biologists, robotics experts) and align technical decisions with broader business goals.
- Experience with or willingness to adopt containerization and CI/CD frameworks for GPU-accelerated code.
- Flexibility to drive innovation while adhering to established processes, design principles, and coding standards.
Delivering Results
- Comfortable working in an agile, fast-paced environment with multiple priorities.
- Track record of on-time delivery for mission-critical software projects.
- Adept at project planning, setting realistic milestones, and communicating progress effectively to stakeholders.
Architecture and Design
- Strong understanding of low-level graphics engine design and GPU memory management.
- Skilled at decomposing complex rendering challenges into modular, maintainable solutions.
- Keen eye for optimizing rendering pipelines for concurrency, resource usage, and speed.
Artifacts, Coding, and Documentation
- Produce high-quality technical artifacts including design docs, code, and performance test results.
- Write secure, stable, testable, maintainable shader and C++ code with minimal defects.
- Follow best practices for version control, continuous integration, and peer review.
Thought Leadership and Communication
- Demonstrate leadership by mentoring peers, guiding best practices in GPU rendering, and driving continuous improvement.
- Communicate complex GPU and rendering concepts to both technical and non-technical audiences.
- Eager to contribute to the broader visualization community through potential open-source contributions, conference presentations, or publications.
Adaptability and Growth
- Enthusiasm for learning new technologies (e.g., advanced shader techniques, compute shaders, domain-specific imaging libraries).
- Ability to adapt quickly to evolving company and industry needs.
- Excitement for the possibility of merging gaming engine workflows (Unity, Unreal) with advanced scientific visualization tasks.
Qualifications
- Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, or a closely related field (or equivalent experience).
- 2+ years of industry experience in real-time rendering, GPU shader development, or a similar role.
- Proficiency in C++ (modern standards preferred) and Vulkan (or proven experience in OpenGL with a desire to learn Vulkan).
- Familiarity with graphics debugging and profiling tools.
- Experience with GPU-accelerated computing beyond graphics (e.g., CUDA, compute shaders) is a plus.
- Proven track record of building functional, high-performance user interfaces for complex 3D visualization applications, leveraging frameworks such as ImGui.
- Experience with hierarchical caching, progressive loading, or compression pipelines is highly desirable.
- Strong communication and collaboration skills, with the ability to translate user needs into technical requirements.
- Demonstrated ability to balance trade-offs between image quality, performance, and resource constraints.
- Passion for advancing scientific discovery through cutting-edge visualization technology.
Preferred Qualification
If you are an experienced GPU shader developer who thrives on optimizing large-scale 3D rendering pipelines for high-impact scientific applications—and you’re excited to collaborate with world-class biologists, engineers, and AI scientists—we encourage you to apply. Join us at Vivodyne and help bring instant, detailed views of human tissue to the hands of the researchers who will use them to transform drug discovery and improve patient outcomes worldwide.