Senior Developer Relations Manager, Digital Health AI Research

NVIDIA•Santa Clara, CA

1d•$224,000 - $431,250

About The Position

We are seeking a highly technical and strategic Senior Developer Relations Manager to join NVIDIA Digital Health, with a focus on engaging researchers and AI developers across industry and academia who are building AI for digital health. In this pivotal role, you will work directly with healthcare AI developers to champion the adoption of NVIDIA’s AI and accelerated computing platforms. The ideal candidate brings a blend of deep research expertise combined with a passion for developer advocacy and a talent for communicating how NVIDIA technology can solve complex, research and real-world deployment challenges. A core initial mission will be to help drive a collaborative digital health consortium focused on industry-relevant benchmarks and synthetic evaluation recipes for digital health AI models and agents.

Requirements

MS or Ph.D degree or equivalent experience in Computer Science, Machine Learning, Clinical Informatics, Computational Medicine, Data Science, Electrical Engineering, Applied Math, or a related technical field.
A minimum of 12+ years of overall professional experience in AI/ML, applied research, software engineering, developer relations, technical partnerships, product management, or solution architecture, including 5+ years of direct hands-on experience in healthcare AI, digital health, or life sciences AI.
Proven track record in leading developer programs across healthcare research organizations.
Significant technical depth in AI tools and model architectures including LLMs, VLMs, speech models, agentic workflows, pre+post-training, and inference optimization.
Experience leading research collaborations with engineering, product, and research teams, including architectural design, model evaluation, benchmark design, code reviews, technical mentorship, and delivery of technical talks or workshops.
Ability to structure and implement technical engagements, negotiate requirements, prioritize issues, and collaborate with internal or external collaborators across product, engineering, research, sales, legal, privacy, and marketing teams.
Skilled at distilling deeply technical concepts for audiences from researchers and engineers to product leaders and executives, with high empathy for developers and researchers and comfort working in a fast-paced, highly matrixed environment.

Nice To Haves

Hands-on experience building or optimizing AI solutions, such as clinical foundation models, healthcare speech systems, or digital health agents in production or research settings.
Familiarity with accelerated computing and AI platforms relevant to healthcare AI, such as NeMo, Nemotron, MONAI, Parabricks and BioNeMo.
Successful history of building and scaling developer communities and research collaborations in healthcare AI.
Expertise in building frameworks to capture developer and researcher sentiment, market shifts, and ecosystem dynamics, translating real-time signals into healthcare AI strategy and product roadmap input.
Published research, patents, standards work, public datasets, open benchmarks, or open-source contributions in healthcare AI.

Responsibilities

Develop and maintain deep technical expertise in digital health AI.
Serve as the trusted technical advisor, problem solver, and champion for researchers and developers across the digital health ecosystem.
Work with cross-functional partners to drive adoption of NVIDIA technologies.
Accelerate digital health AI research workloads by demonstrating and integrating the NVIDIA software stack, including tools, libraries, SDKs, NIMs, and blueprints, into research platforms, applications, and pipelines.
Guide partners and research collaborators through onboarding and integration by providing technical resources such as sample code, evaluation harnesses, training recipes to accelerate research and foster co-innovation.
Map and monitor the researcher ecosystem to identify growth opportunities, including healthcare AI agents, foundation models, model evaluation, synthetic data generation, post-training, inference, and deployment tooling.
Engage research leaders across academia and industry to drive best-practice integrations, resolve technical challenges, surface new workflows, and channel critical field insights back to NVIDIA product teams.
Help create open benchmark datasets, reproducible synthetic data generation pipelines, model evaluation harnesses, fine-tuning recipes, technical papers, and blogs.
Represent NVIDIA at research conferences, industry forums, hackathons, technical meetups, and partner events while supporting early access programs, product launches, go-to-market activities, and lighthouse collaborations.