NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.
We are looking for a Principal Engineer to set the technical direction for raw-to-insights medical imaging: AI and signal-processing systems that operate directly on raw acquisition data (MRI k-space, CT projection data, PET list-mode, and other modalities) rather than on already-formed images. This is a founding, strategy-shaping role. You will define the reconstruction and acquisition-AI charter across our imaging stack, build the platform and standards that let an ecosystem build on top of your work, and partner closely with our existing ultrasound reconstruction effort to cover the full acquisition layer. If you have built systems that moved imaging computation beyond the scanner and want to do it at industry scale to empower all medical imaging manufacturers, this role is for you.
What you'll be doing:
Defining the technical and architectural strategy for medical image reconstruction and raw-to-insights AI across modalities (MRI, CT, PET), and establishing the reference architecture for imaging reconstruction on Holoscan and accelerated compute.
Designing and guiding GPU-accelerated, real-time and distributed reconstruction pipelines that span edge devices and shared cloud compute, with the latency, throughput, and reliability that clinical use demands.
Advancing AI-based reconstruction, denoising, motion correction, and uncertainty quantification — pushing image quality and trustworthiness from accelerated acquisitions.
Driving raw-data access, interoperability, and standardization (cross-vendor acquisition formats, AI-ready datasets) so that researchers and partners across the ecosystem can build on a common foundation.
Partnering with the ultrasound raw-to-insights lead so the modalities are complementary, the platform philosophy is shared, and the combined effort covers the entire acquisition layer end to end.
Serving as a company-level technical authority: influencing product and research strategy across multiple teams, representing NVIDIA to clinical, academic, and OEM partners, and mentoring senior engineers and researchers.
Translating clinical and partner needs into architecture, then owning the decisions that determine the success of the reconstruction platform.
What we need to see:
PhD in biomedical/electrical engineering, computer science, medical physics, or related field (or equivalent experience), and 12+ years of relevant experience building computational imaging or signal-processing systems.
Recognized and sought-out for expertise in reconstructing medical images and understanding image formation physics. Proficient in at least one modality (MRI, CT, or PET) at the raw-signal level (e.g., k-space, projection, or list-mode data).
Deep, hands-on command of GPU-accelerated computing and the infrastructure required to deploy reconstruction at scale (C++ and/or Python, CUDA, real-time/streaming pipelines, edge-to-cloud architectures).
A track record of building platforms, frameworks, or open-source systems that created leverage for an ecosystem beyond your immediate team — not just publications or one-off models.
Fluency with modern deep-learning methods for inverse problems (reconstruction, denoising, super-resolution) and a clear point of view on validation, uncertainty, and clinical trustworthiness.
The ability to operate as a cross-organization technical leader: setting direction, influencing through others, and shaping strategy at the department and company level.
Ways to stand out from the crowd:
You have created widely adopted open-source reconstruction software or community data standards that others build on.
Familiarity with healthcare deployment realities: clinical workflow integration, regulatory/validation pathways, and security and compliance for patient data.
A history of working across academia, clinical sites, and instrument manufacturers, and of moving research prototypes into real deployment.
Exposure to physics-informed AI, foundation models operating on raw signals, or adjacent simulation and synthetic-data work
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and talented people in the world working for us. If you're creative and passionate about developing cloud services we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Based on 3,388 disclosed Healthcare salaries on RoleSuite, the role pays a median of $110K/year, with most offers between $87K and $166K (10th–90th percentile: $67K–$250K).
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