Senior Scientist, Synthetic Data Generation

Nvidia

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CANew York, NY
Salary: $168,000–$264,500 / yr
Posted: 5 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $168k

This role $216k

$99k most similar roles pay here $282k

This role pays more than 78% of similar roles. Most pay $126,800–$209,000 — the shaded band above. At the midpoint, this role pays about $216k versus about $168k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 994 open roles on FindRole.

Listed pay typically runs $168,000–$270,250 across 977 roles with salary data.

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At a glance

TL;DR · Senior Scientist, Synthetic Data Generation

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As a Senior Scientist at NVIDIA, you will join the cutting-edge research team focused on advancing large language models through synthetic data generation. Your daily work involves building sophisticated pipelines using LLM-based methods to create high-quality datasets that enhance pre- and post-training processes for models like Nemotron. You’ll collaborate closely with various teams to develop open-source libraries within the NeMo ecosystem, ensuring they are well-documented and accessible. Key responsibilities include advancing multimodal synthetic data generation techniques, driving software excellence through modern tooling, and publishing research at top AI conferences. Ideal candidates hold a PhD in Computer Science or related fields, have extensive experience in synthetic data generation and generative modeling, and possess strong publication records and open-source contributions. Experience with multimodal understanding and scalable data pipelines is highly valued.

Skills

Python LLM-based methods Git CI/CD vLLM TGI NeMo OpenAPI Docker Kubernetes AWS GCP Azure PostgreSQL MongoDB TensorFlow PyTorch Hugging Face Transformers Apache Airflow

What you'll do

Build synthetic data generation pipelines using LLM-based methods to enhance pre- and post-training of models like Nemotron.
Advance multimodal synthetic data generation techniques for images, documents, videos, and audio in collaboration with model teams.
Design and maintain open-source libraries with clean APIs and strong documentation within the NVIDIA NeMo ecosystem.
Publish original research at top machine learning and AI conferences to uphold technical leadership.
Mentor interns and junior researchers to foster technical growth within the team.

What we're looking for

PhD in Computer Science, Machine Learning, Statistics, or related field with 3+ years research experience.
Expertise in synthetic data generation, generative modeling, and multimodal machine learning.
Deep understanding of LLMs and their pre/post-training processes using inference frameworks.
Proven track record developing software libraries used by broad developer communities.
Strong publication history at top AI conferences like NeurIPS, ICML, ICLR, ACL.
Experience with multimodal data generation and scalable data pipeline optimization.

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