招聘
Required Skills
Python
PyTorch
Medical imaging
Deep Learning
MONAI
DICOM
AI development
We are looking for a Solutions Architect to work with AI for Healthcare and Life Sciences in Taiwan, focused on academic society to adopt NVIDIA GPU platform on VLM, Digital Twin, AI, Accelerated Analytics, Simulation, Deep Learning or Machine learning technologies. NVIDIA’s platform for HPC/MIG and Omniverse (OM), deep learning and high-performance computing have already made a major impact on industry. At NVIDIA, our Solution Architects are drawn from elite developers and scientists who enjoy working with the latest GPU hardware and software. We need a passionate, hard-working, and creative individual to help us pursue more of these opportunities in fields. Your primary focus is on AI for Sciences with researchers and developers at universities, research institute and labs.
What you'll be doing:
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Design and implement end‑to‑end AI pipelines for medical imaging, sensor fusion, and real‑time inference using platforms such as MONAI, Holoscan, and Clara.
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Collaborate with hospitals, academia, med‑tech, and health‑IT partners to translate clinical workflows into deployable, regulatory‑compliant AI systems.
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Build reusable reference architectures and toolkits for imaging, robotics‑assisted surgery, and smart‑hospital applications.
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Optimize model performance and deployment on NVIDIA platforms including DGX, IGX, and edge systems powered by Holoscan.
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Lead proof‑of‑concept and production projects with healthcare customers, ensuring reliability, scalability, and data‑security compliance.
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Partner with internal teams to scale validated AI architectures and best practices across the healthcare ecosystem.
What we need to see:
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Master’s degree or Ph.D. in Computer Science, Biomedical Engineering, or related field.
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6 years of experience in AI development, medical imaging, or edge‑computing applications.
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Proficient in Python and deep learning frameworks such as Py Torch, with hands-on experience using MONAI for medical imaging model training, inference, and optimization.
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Familiarity with DICOM, PACS/VNA systems, and clinical‑data integration workflows.
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Strong proficiency in Python and experience deploying AI on GPU‑accelerated platforms.
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Excellent communication and technical leadership skills.
Ways to stand out from the crowd:
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Experience with MONAI, Holoscan, Clara, or related NVIDIA healthcare SDKs.
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Knowledge of medical‑device development cycles or TFDA/FDA regulatory frameworks.
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Background in real‑time or low‑latency vision and sensor‑processing pipelines.
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Proven track record delivering AI solutions in clinical or hospital environments.
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About NVIDIA

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
Employees
Santa Clara
Headquarters
$4.57T
Valuation
Reviews
4.1
10 reviews
Work Life Balance
3.5
Compensation
4.2
Culture
4.3
Career
4.5
Management
4.0
75%
Recommend to a Friend
Pros
Great culture and supportive environment
Smart colleagues and excellent people
Cutting-edge technology and learning opportunities
Cons
Team-dependent experience and outcomes
Work-life balance issues with long hours
Politics and influence over competence
Salary Ranges
47 data points
Junior/L3
Mid/L4
Junior/L3 · Analyst
7 reports
$170,275
total / year
Base
$130,981
Stock
-
Bonus
-
$155,480
$234,166
Interview Experience
7 interviews
Difficulty
3.1
/ 5
Experience
Positive 0%
Neutral 86%
Negative 14%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Interview
5
System Design Interview
6
Team Review
Common Questions
Coding/Algorithm
System Design
Technical Knowledge
Behavioral/STAR
News & Buzz
Negotiating NVIDIA's Offer
Base, stock, and sign-on negotiable. Recruiters invested in closing candidates. CEO reviews all 42K employee salaries monthly. Stock growth has made many employees millionaires.
News
·
NaNw ago
NVIDIA Company Reviews
WLB rated 3.9/5 (lowest category). 64% satisfied with WLB but 53% feel burnt out. Compensation rated 4.4-4.5/5. Experience highly team-dependent.
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·
NaNw ago
NVIDIA Culture Discussions
Team-dependent experience; sink-or-swim culture that rewards high performers but can be overwhelming. No politics, flat structure, but demanding workload with some teams requiring evening/weekend work.
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·
NaNw ago
NVIDIA Interview Discussions
Technical bar is high with 4-6 rounds. Process takes 4-8 weeks. Expect C++ questions, LeetCode medium, and system design. Difficulty rated 3.16/5.
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NaNw ago