Senior Applied Research Scientist, Data Curation - Remote
$224,000 - $356,500 USD yearly
Originally posted 27 August 2026 by the employer.
Join the team working on data curation and document extraction pipelines for foundation-model training, including capabilities that power NVIDIA Nemotron Parse.
About the role
This role involves researching, developing, and deploying deep learning models at scale for data curation and document extraction pipelines. The work focuses on structured content extraction, data quality, and deduplication at petabyte-scale for training Nemotron LLM models.
What you'll do
- Develop efficient models and data pipelines to extract and curate multi-modal data (documents, image, audio, videos) for foundation model training.
- Build pipelines for petabyte-scale extraction and content deduplication, including document and HTML parsing, fuzzy and semantic deduplication.
- Expand and optimize curation methodologies for petabyte-scale multimodal data on hundred-node GPU clusters to improve foundation model training sets.
- Explore and craft datasets, metrics, experiments, and validation scripts to develop standard methodologies for research.
- Help ML Engineers scale pipelines to production capability through the development of NVIDIA Inference Microservices (NIMs) and blueprints.
- Write papers, blog posts, documentation, and training materials to help customers understand and utilize research.
What you'll need
- Master's, Ph.D., or equivalent experience in data curation, document AI, information retrieval, or multimodal research with a track record of publication in leading conferences.
- Hands-on experience developing computer vision and document-extraction models and pipelines, including layout analysis, OCR, and table, figure, or formula extraction.
- 10+ years of experience developing multimodal systems across a range of models and platforms.
- Expertise managing distributed data frameworks like Ray, Spark, or Dask, and deploying massive, multi-node machine learning or data processing tasks in production.
- Knowledge of best practices in batching, streaming, and scaling of ingestion pipelines.
- Excellent Python programming skills and strong hands-on experience with PyTorch or comparable modern deep learning frameworks.
Nice to have
- Information retrieval experience.
- History of mentoring junior engineers and interns.
Skills: data curation, foundation-model training, petabyte-scale, multi-modal data, GPU clusters
This role has been open 51 days — exactly the 51-day median for Infrastructure/Platform Software roles.
Infrastructure/Platform Software · Infrastructure Platform
|
Open roles in category
962
|
Median days open
51 d
|
Median salary
$236k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | NVIDIA | All employers we track in this specialty (962 roles · 86 employers) |
|---|---|---|
| Open roles in this specialty | 278 | 962 |
| Open roles in the wider Software, Firmware & Systems family | 971 | 6118 · 145 employers |
| Median days open | 46 d | 51 d (−5 d vs this employer) |
| Median salary (USD postings) | — | $236k |
Skills observed across this category: data curation, foundation-model training, petabyte-scale, multi-modal data, GPU clusters
Who's hiring in this category
- NVIDIA (this employer) · 274 open roles · median 47 d
- Qualcomm · 62 open roles · median 53 d
- AMD · 54 open roles · median 19 d
- Graphcore · 44 open roles · median 93 d
- Intel Corporation · 43 open roles · median 12 d
- Cerebras · 36 open roles · median 83 d
How we counted: 962 open Infrastructure/Platform Software (Infrastructure Platform) roles from 86 employers tracked in the SemiconductorJobs index, counted 18 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.