{"id":203154,"url":"https://alion.io/job/nvidia-principal-research-scientist-synthetic-data-generation","title":"Principal Research Scientist, Synthetic Data Generation","company":{"id":6,"name":"NVIDIA","domain":"nvidia.com","url":"https://alion.io/company/nvidia","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":80,"open_postings":829,"ghost_share":0.023,"stale_share":0.739,"repost_share":0.042,"time_to_fill_p50_days":35,"computed_at":"2026-10-27T05:46:45Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Santa Clara, United States","New York, United States","United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":272000,"max":431250,"currency":"USD","period":"year","gross":null,"usd_annual":431250},"salary_estimate":null,"experience_years_min":15,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NVIDIA NeMo","optional":false},{"name":"Post-training","optional":false},{"name":"Pre-training","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Synthetic Data","optional":false},{"name":"TGI","optional":false},{"name":"vLLM","optional":false}],"status":"live","first_seen_at":"2026-09-04T21:53:16Z","employer_posted_date":"2026-09-04","last_verified_at":"2026-10-27T13:24:21Z","board_verified":true,"closed_at":null,"days_open":52,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":52},"description":"NVIDIA is at the forefront of the AI revolution, and our research is shaping the future of large language models. We are looking for a Principal Scientist to set the technical direction for synthetic data generation across NVIDIA's frontier model efforts. You will define and build open-source libraries within the NVIDIA NeMo ecosystem that generate synthetic datasets across text, code, structured, and multimodal data, feeding the pre- and post-training of LLMs such as Nemotron. This role combines hands-on software engineering with applied research in generative methods, and you will collaborate with research, engineering, product, and model teams as well as external labs.\nWhat you'll be doing:\nBuild and scale data generation pipelines using LLM-based methods combined with automated quality evaluation. resulting in datasets to improve both initial training and fine-tuning of LLMs such as Nemotron. These data pipelines cover reasoning, coding, structured output, and multimodal understanding.\nPioneer data generation for agentic and tool-use training: synthetic trajectories, multi-turn interactions, function calling, and executable environments for reinforcement learning, including reward modeling and verifiable-reward data\nAdvance multimodal synthetic data generation - image, document, video, and audio - in partnership with NVIDIA's model teams.\nAdvance privacy-preserving and safe synthesis - differential privacy, anonymization, and de-identification - enabling model training on sensitive data in regulated domains.\nDevelop and maintain open-source libraries and SDKs with clean APIs and strong documentation.\nDrive software excellence with modern tooling, architecture based on configuration, and professional Git/CI-CD.\nPublish original research at top machine learning and AI conferences to maintain NVIDIA's technical leadership.\nMentor scientists and engineers across the team, raising the technical bar and growing the next generation of researchers.\nWhat we need to see:\nPhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent experience.\n15+ years of engineering and research experience in synthetic data generation, generative modeling, multimodal machine learning, or related areas.\nDeep technical understanding of LLMs, how data shapes their pre-training, post-training, and RL stages, and inference frameworks such as vLLM or TGI.\nProven track record of developing or maintaining software libraries used by a broad developer community.\nExperience building and optimizing scalable data pipelines for large-scale model training - throughput, distributed inference, and cost at cluster scale.\nStrong publication record at premier venues such as NeurIPS, ICML, ICLR, ACL or similar.\nWays to stand out from the crowd:\nSignificant open-source contributions in ML or data tooling, with community adoption.\nExperience with multimodal generation or understanding (vision-language, document AI, video, or audio).\nExperience generating data for agentic, tool-use, or reinforcement-learning post-training, including RL environment design.\nBackground in differential privacy, de-identification, or synthetic data for regulated industries such as healthcare, finance, or government.\nExperience influencing model training decisions at frontier scale, or partnering directly with pre-training and post-training teams.\nNVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and talented people in the world working with us. If you are creative, autonomous, and passionate about building open-source tools that make AI safer and more private, we want to hear from you.\nYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.You will also be eligible for equity and benefits.\nApplications for this job will be accepted at least until September 8, 2026.This posting is for an existing vacancy.\nNVIDIA uses AI tools in its recruiting processes.\nNVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. 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