Nvidia
Healthcare
LeadEngineer,HealthcareDataOperationsandStrategy
“Lead Engineer, Healthcare Data Operations and Strategy at Nvidia. Skills: Healthcare data operations, Healthcare data strategy, MLOps platform architecture and development, Data governance, Cross-functional collaboration. Define a portfolio strategy and selection methodology for NVIDIA's healthcare data programs with key collaborators. Prioritize modalities, clinical domains, and partner cohorts based on scientific and market impact, downstream model value, partner readiness, and technical feasi”
What You'll Achieve.
Establish the MLOps backbone that makes each program a durable, growing asset; Ensure data programs are sequenced and crafted to feed the highest-priority needs; Meet the regulatory and compliance expectations of global clinical partners
Industry & Context.
What They're Looking For.
Must Have
12+ years working with healthcare data — building datasets, running data programs, or leading MLOps workflows in a healthcare or medtech setting, technical proficiency across the healthcare data lifecycle: ingestion, curation, annotation, de-identification, governance (HIPAA, GDPR, IRB workflows), and serving for training and evaluation, Hands-on experience with MLOps tooling — data lakes/lakehouses, dataset versioning (e. g. , Hugging Face Datasets, LakeFS, DVC), workflow orchestration, validation frameworks — and a clear point of view on when to build versus integrate, Familiarity operating at the intersection of strategy, partnerships, and engineering — able to set portfolio direction one day and review schema choices or pipeline architectures the next, BS or higher in Computer Science, Biomedical Engineering, Computational Biology, or a related technical field, or equivalent experience
Nice to Have
Direct healthcare industry experience — including familiarity with how device data is generated, retained, and released, Track record of launching publicly released, commercially usable healthcare datasets, Experience standing up data infrastructure for foundation model training, including multi-modal sensor data, Deep relationships across the global clinical AI community (MedTech or biopharma), and a history of converting those relationships into shipped artifacts, Familiarity with NVIDIA platforms relevant to healthcare AI — Holoscan, BioNeMo, Cosmos, Isaac, NeMo Data Designer, or Omniverse
What You'll Do.
Define a portfolio strategy and selection methodology for NVIDIA's healthcare data programs with key collaborators
Prioritize modalities
and partner cohorts based on scientific and market impact
downstream model value
and technical feasibility
Drive the tactical execution of new healthcare data collaborations end-to-end: prioritizing
data contribution agreements and licensing
contribution standards
Architect and build our healthcare data MLOps platform that ingests
and serves multi-institution healthcare data at scale
Combine NVIDIA's internal tooling with outstanding external systems when appropriate
Partner directly with NVIDIA healthcare and model training teams (e. g.
Cosmos) to ensure data programs are sequenced and crafted to feed the highest-priority needs
Establish data quality
and governance standards that scale across modalities and meet the regulatory and compliance expectations of global clinical partners
How You'll Work.
Team & Collaboration
Collaborate with community partners; Connect leading clinicians, academic researchers, medtech industry partners, and NVIDIA's engineering and product teams; Partner directly with NVIDIA healthcare and model training teams (e. g. , GR00T, Cosmos); Partner with key collaborators
Process & Methodology
Drive the tactical execution of new healthcare data collaborations end-to-end
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