{"id":2786294,"url":"https://alion.io/job/nvidia-mlops-physical-ai-data-intern-2027","title":"MLOps Physical AI Data Intern - 2027","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":82,"open_postings":592,"ghost_share":0.019,"stale_share":0.66,"repost_share":0.034,"time_to_fill_p50_days":33,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Early Careers","role_family":"Early Careers","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Shanghai, China"],"countries":["CN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":22000,"max_usd":44000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":710},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"C++","optional":false},{"name":"Computer Vision","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Physical AI","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-10-12T00:00:00Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-18T01:32:53Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"NVIDIA is building the next generation of AI and advanced data technologies for Physical AI. Our MLOps GT team designs large-scale data infrastructure, LLM models and agents powering Ground Truth (GT) generation, and end-to-end AI workflows for global automotive and robotic partners. We're looking for a motivated MLOps Physical AI Data Intern to help build, scale, and optimize this global data ecosystem while driving strong collaboration across engineering, operations, and research teams.\nWhat You’ll Be Doing:\nContribute to the development of distributed data pipelines supporting large-scale GT generation and global data distribution.\nSupport the integration of international datasets (vision, LiDAR, map, and sensor) for multi-region model development and validation.\nDevelop GT auto labeling, LLM models, and a variety of AI Agents for the global GT generation.\nHelp design tools for monitoring data quality, job status, and progress tracking within the global GT release pipeline.\nParticipate in continuous improvement initiatives for platform scalability, performance tuning, and workflow automation.\nWhat We Need to See:\nCurrently pursuing a BS, MS, or PhD in Computer Science, Software Engineering, Data Engineering, or a related field.\nSolid programming experience with Python and C++.\nGood understanding of computer vision, AI agent development, LLM and machine.\nAnalytical and problem-solving abilities, with an interest in large-scale AI data ecosystems.\nGood communication and teamwork skills, especially for collaboration across global and multi-disciplinary teams.\nWays to Stand Out from the crowd:\nProficient in developing AI agents.\nExperience in Physical AI data engineering, or MLOps.\nPrior exposure to autonomous driving data, computer vision, or machine learning pipelines.\nHands-on experience with Physical AI modeling, GT data processing.\nAt NVIDIA, interns are integral to real-world projects that push the boundaries of Physical AI. 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