FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates deep expertise in AI applications, particularly Generative AI and Physical AI, within scientific domains, while effectively translating research insights into actionable strategies for product development and ecosystem growth.
Highest-signal resume keywords
PhD In Computer ScienceExperience In AI And Machine LearningExpertise In NVIDIA TechnologiesEstablished Research CredibilityStrong Understanding Of Computational Science
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI Application DevelopmentResearch MethodologyModel API UtilizationOrchestration ToolsSandboxed ExecutionHigh-Impact PublicationOpen-Source Software ContributionTechnical Content CreationEmerging Research Trend IdentificationCollaboration With Academic Labs
Soft Skills
Interpersonal Dynamics UnderstandingCross-Functional CollaborationTechnical DirectionCommunication SkillsStrategic Opportunity Identification
Tools & Technologies
CUDANVIDIA AI EnterpriseNeMo/NemotronBioNeMoCuQuantumOmniverseIsaacRAPIDSTensorRT-LLMDGX Systems
Industry Keywords
Generative AIPhysical AIComputational ScienceScientific WorkflowsResearch EcosystemInnovation AdvancementAcademic ConferencesResearch WorkshopsTechnical SummitsEcosystem Growth
About the role
Key responsibilities & impact- Act as a trusted technical advisor for research labs, engaging and partnering with ecosystem leaders
- Identify and accelerate high-impact workloads by integrating NVIDIA's frameworks, libraries, and core software stack into research projects
- Map and continuously assess the research ecosystem to identify institutional growth opportunities and inform long-term technology strategies
- Stay current on research papers across affiliated domains to anticipate emerging trends and provide technical direction on future collaboration areas
- Collaborate cross-functionally with Research Account Managers, Solution Architects, and Business Development teams to drive researcher enablement
- Forge closer ties with lab personnel by understanding opportunities, challenges, interpersonal dynamics, and the full scope of research being conducted
- Attend domain scientific conferences and facilitate NVIDIA participation alongside other subject matter experts
- Drive success stories into adoption
- Represent researchers' needs internally by translating academic feedback into actionable insights for product development, education programs, and platform roadmaps
Requirements
What you’ll need- PhD in Computer Science, AI, Machine Learning, Computational Science or a related technical field; or equivalent experience demonstrating comparable research depth
- Over 4+ years of experience in research or industry, with a proven record of advancing innovation at the crossroads of AI and Science
- Deep expertise in applying AI, including Generative AI and Physical AI, to a specific scientific domain
- Broad intellectual foundation to translate AI breakthroughs across Biology, Physics, material science and complex scientific workflows
- Strong understanding of frontier research challenges in AI and computational science
- Hands-on experience building or evaluating AI systems using modern frameworks, model APIs, orchestration tools, retrieval systems, and sandboxed execution for research-grade deployment
- Established research credibility evidenced by high-impact publications, contributions to open-source scientific software, or successful collaborations with academic laboratories
- Experience with NVIDIA technologies and platforms such as CUDA, CUDA-X libraries, NVIDIA AI Enterprise, NIM, NeMo/Nemotron, BioNeMo, cuQuantum, Omniverse, Isaac, RAPIDS, TensorRT-LLM, Dynamo, or DGX/accelerated computing systems
- Established relationships with leading academic labs, research institutes, national labs, or major open-source research communities
- Track record translating frontier research into demos, reference architectures, workshops, technical content, or developer enablement programs
- Experience presenting at academic conferences, research workshops, technical summits, or university-facing events
- Ability to identify emerging research trends and convert them into strategic opportunities for collaboration, platform adoption, and ecosystem growth
Benefits
Comp & perks- Competitive salaries
- Generous benefits package
- Equity