Senior Software Engineer - Enterprise Data
$168k - $322k • Remote • US, CA, Santa Clara
Posted 4d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
NVIDIA is seeking a Staff Engineer to develop the company's Enterprise Data Governance platform. This platform is crucial for protecting sensitive information, managing data access across all collaboration and content systems, and building a knowledge infrastructure that ensures the trustworthiness and accuracy of enterprise AI. The role presents a unique challenge in balancing the need for broad data access for AI agents with strict security, legal, and export control requirements. This position is ideal for technically strong engineers at the senior to principal level who are passionate about solving complex infrastructure problems and contributing to NVIDIA's core operations at scale.
Responsibilities
- Define and manage the roadmap for sensitive information detection and remediation, collaborating with Finance, Legal, and Security.
- Evaluate and integrate ML models for sensitive content classification in unstructured data at scale.
- Drive the rollout and adoption of the enterprise data access platform, including connectors for various communication and document systems.
- Design and implement export control enforcement and audit logging mechanisms.
- Integrate enterprise content sources into the AI knowledge platform to ensure data accuracy and appropriate access scoping for AI agents.
- Establish and enforce content ingestion quality standards.
- Provide technical leadership, making architectural decisions and resolving ambiguities.
- Improve engineering practices through code and design reviews, and mentorship.
Requirements
- Bachelor's or Master's Degree in Computer Science, Computer Engineering, or a related field (or equivalent experience).
- 8+ years of experience building and operating large-scale enterprise platforms.
- Strong foundation in backend systems, distributed systems, and data engineering, including large-scale data processing and indexing pipelines.
- Experience building or integrating data connectors or enterprise SaaS integrations.
- Experience training and evaluating ML models for classification tasks, particularly in security or content sensitivity.
- Strong communication skills to translate technical tradeoffs to non-technical stakeholders.
- Ability to make decisions with incomplete information and adapt to shifting priorities.
Benefits
- Equity
- Benefits