Nvidia Senior Solution Architect - Medical Devices 

Germany, North Rhine-Westphalia 

673716193

In this role, you will serve as a trusted technical advisor and leader, working with our customers who recognize the transformative potential of accelerated computing and artificial intelligence in the healthcare domain. You will develop innovative proof-of-concept demonstrations and establish strategic relationships with key executives to advocate for the integration of AI and accelerated computing at both the edge and in the cloud. By engaging with a diverse group of developers, researchers, data scientists, and IT leaders, you will contribute to impactful projects and help shape the narrative of AI in healthcare.

What you will be doing:

• Partner with our business/account team working with customers to develop a keen understanding of their goals, strategies, and technical needs and to help define and deliver high-value solutions meeting these needs.

• Work to design NVIDIA's HW/SW into next generation software defined medical devices and physical AI enabled surgical robotics.

• Stay up to date on the state of the art in image analysis, sensor processing, robotics & surgical data science to apply the latest advancements in the field to customer needs.

• Support customers to optimize workloads using NVIDIA’s computing platform.

• Document what you know and teach others. This can vary from building targeted training for partners and other Solutions Architects, to writing whitepapers, blogs, and wiki articles, to simply working through hard problems with a customer on a whiteboard.

• Partner strategically with lighthouse customers and industry-specific solution partners targeting our computing platform.

• We make heavy use of conferencing tools, but some travel is required for this role. You are empowered to find the best way to get your job done and make our customers successful.

What we need to see:

• Strong foundational expertise: MS, PhD or equivalent experience in Computer Science, Mathematics, Biomedical Engineering, Electrical Engineering, or closely related fields.

• 5+ years of work-related experience in software development, machine learning, deep learning or high-performance computing.

• In-depth knowledge and practical experience with contemporary Deep Learning software architecture and frameworks, in particular regarding image and video processing of medical and surgical modalities.

• Experience in scientific computing and software development with C/C++, Python, or CUDA. Skilled in streaming data processing, performance analysis, and optimization from algorithms to pipelines.

• Strong time-management and organizational skills for coordinating multiple initiatives, priorities, and implementations of new technology and products into very complex projects.

• Excellent communication skills particularly in the presentation of highly technical material. Must enjoy interacting with forward-thinking people, life-long learning, and staying at the forefront of the domain.

Ways to stand out from the crowd:

• Domain expertise and proven hands – on experience applying accelerated computing and AI in one of the following areas: medical imaging, digital surgery, surgical data science, or medical robotics. Familiarity with clinical workflows, interventional and/or surgical procedures.

• Industry experience with medical device development life cycle or developing SW in regulated environments. Understanding of regulatory requirements (e.g., HIPAA) and data privacy concerns specific to healthcare data.

• Extensive deep learning knowledge with practical experience with relevant frameworks and model architectures (e.g., CNNs, LLMs, VLMs, VLAs), training robotic policies, training from simulation / Digital Twins. Proficiency in deploying AI models and optimizing inference using TensorRT, ONNX Runtime, Triton, or TensorRT-LLM is a plus.

• Proven experience implementing and optimizing workloads with CUDA and Nsight Tools. Experience with high performance networking technologies, e.g. DPDK, DOCA, RMDA, RoCEv2 is a plus.

• Published record of thought leadership in a technical area or industry segment.