Senior Scientist, Synthetic Data and Privacy

About the role

NVIDIA is seeking a Senior Scientist to lead the development of synthetic data generation and privacy-preserving AI technologies within the NVIDIA NeMo ecosystem. This role involves creating and optimizing LLM-based methods for generating synthetic data, enhancing data privacy, and implementing context-aware anonymization techniques. The successful candidate will collaborate with various teams to ensure these advancements are integrated into real-time applications.

Responsibilities

• Develop LLM-based methods for synthetic data generation, privacy, and context-aware anonymization, with automated evaluation across multilingual text, documents, and multimodal content.
• Optimize task-specific LLMs for low-latency, high-throughput inference (distillation, quantization), and scale our frameworks to run in real time.
• Design and maintain open-source libraries and SDKs with clean APIs and strong documentation.
• Drive software excellence with modern tooling, architecture based on configuration, and professional Git/CI-CD.
• Publish original research at top machine learning and AI conferences to maintain NVIDIA's technical leadership.
• Mentor interns and junior researchers to develop technical growth within the team.

Requirements

• PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent experience.
• Research background of 2+ years in applied LLM/NLP research and engineering, synthetic data generation, anonymization and PII detection, or related areas.
• Proven track record of developing or maintaining software libraries used by a broad developer community.
• Strong publication record at premier venues such as NeurIPS, ICML, ICLR, ACL or similar.

Qualifications

• Active contributions to open-source projects, particularly in ML, security, or privacy domains.
• Deep technical understanding of LLMs and inference optimization (quantization, distillation, latency/throughput tuning), with frameworks such as vLLM or TGI.
• Functional knowledge of global privacy regulations such as GDPR or CCPA.

Skills

• Experience with LLMs and their applications in synthetic data generation and privacy.
• Proficiency in software development and open-source library maintenance.
• Knowledge of global privacy regulations and their impact on AI development.

Benefits

• Competitive base salary ranging from $168,000 to $264,500 for Level 3, and $192,000 to $304,750 for Level 4.
• Equity and comprehensive benefits package.

Pay

• Base salary range: $168,000 - $264,500 for Level 3, and $192,000 - $304,750 for Level 4.

Schedule

• Full-time position.

Benefits

• Comprehensive benefits package.