NVIDIA is seeking an Applied AI Innovation Engineer to develop innovative AI solutions. You will evaluate NVIDIA AI capabilities against real-world use cases, collaborate with technical and business teams, and provide recommendations to shape the Sales AI Applications roadmap.
Responsibilities:
- Collaborate with Solution Architects, Sales, Product, Engineering, and Data teams to understand use cases and explore potential AI solutions.
- Develop and test prototypes demonstrating how NVIDIA AI capabilities can improve business and user workflows.
- Establish evaluation criteria, quality metrics, success measures, and test plans for proofs of concept and pilots.
- Perform detailed analyses of technical performance, user experience, adoption potential, and business value.
- Use quantitative data, user feedback, and technical findings to identify opportunities, limitations, tradeoffs, and risks.
- Document findings and communicate recommendations clearly to technical and non-technical team members.
- Provide evidence-based recommendations aligned with business priorities and translate evaluation patterns into roadmap insights.
- Explore generative AI, agentic workflows, retrieval systems, and other NVIDIA technologies that could support use cases.
Requirements:
- Bachelor's degree or equivalent experience in Computer Science, Engineering, Data Science, or a related technical field.
- 2+ years of experience in software engineering, AI or machine learning engineering, solutions engineering, data engineering, technical consulting, or a related area.
- Experience building, testing, or evaluating AI, machine learning, or software prototypes.
- Familiarity with generative AI, APIs, cloud platforms, data workflows, and modern application development.
- Experience using data, experiments, testing, or user feedback to evaluate technical solutions and make recommendations.
- Analytical and problem-solving approach to assessing solutions, comparing tradeoffs, and making evidence-based recommendations.
- Ability to translate business problems into technical approaches and communicate with technical and non-technical audiences.
- Ability to collaborate across teams and organize multiple evaluation efforts with different priorities.
Benefits:
- Equity
- Benefits

