{"id":3431070,"url":"https://alion.io/job/nvidia-senior-manager-training-data","title":"Senior Manager, Training Data","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":81,"open_postings":820,"ghost_share":0.024,"stale_share":0.685,"repost_share":0.046,"time_to_fill_p50_days":36,"computed_at":"2026-10-29T05:49:05Z"}},"role":"Legal","role_family":"Legal","seniority":"senior","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"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":240000,"max":379500,"currency":"USD","period":"year","gross":null,"usd_annual":379500},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Multimodal AI","optional":false},{"name":"Post-training","optional":false},{"name":"Python","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"SQL","optional":false},{"name":"Synthetic Data","optional":false}],"status":"live","first_seen_at":"2026-10-28T00:00:00Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-10-29T05:31:06Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"NVIDIA is seeking a senior product leader to define the strategy and build the platforms that deliver high-quality training data for our foundation models. Starting with web and code data for Nemotron, you will help research teams discover valuable new sources from the open web, improve data quality and diversity, and turn raw content into datasets that advance model capabilities. In this founding product leadership role, you will partner with an engineering lead and work across research, data acquisition, data platforms, and legal teams to build the roadmap and investment priorities. You will connect data acquisition and curation decisions to measurable training outcomes, balancing quality, scale, delivery time, and cost. As research needs evolve, you will extend the platform to additional domains and modalities!\nThis role offers the opportunity to shape a foundational capability for NVIDIA’s AI models, working directly with researchers and engineers to improve what our models can learn. If you bring deep technical curiosity, product judgment, and a record of delivering ambitious data platforms, we want to hear from you.\nWhat you’ll be doing:\nOwn the product vision, strategy, and roadmap for training data acquisition and preparation. Translate research priorities and model capability gaps into source requirements, platform investments, and dataset acceptance criteria aligned with training schedules.\nDefine requirements for source discovery, URL indexing, predictive quality and diversity ranking, crawl scheduling, distributed fetching, and ingestion. Partner with engineering on throughput, reliability, storage, and capacity planning as workloads scale.\nDrive improvements in parsing and curation, including HTML extraction, browser-rendered content, code and math preservation, duplication, quality filtering, and dataset composition. Identify where valuable content is lost and increase the yield of usable, differentiated data.\nLead build, buy, and partner decisions across internal crawling, commercial datasets, and licensed content. Establish comparable internal and vendor pilots that measure incremental coverage, accepted data yield, delivery reliability, and total cost against existing corpora.\nPartner with researchers on controlled training experiments and ablations to measure data impact on model capabilities. Account for benchmark contamination, dataset composition, and regressions, and use results to guide source selection and acquisition investment.\nWork with legal, privacy, policy, and security teams to translate approved requirements into scalable controls for source eligibility, access restrictions, opt-outs, provenance, and permitted use. Define auditable dataset acceptance and release processes.\nBuild researcher-facing capabilities for dataset discovery, metadata, versioning, lineage, and quality reporting. Enable reproducible dataset releases and reuse, measure adoption, and reduce the time from a research request to training-ready data.\nAlign teams on priorities, dependencies, and ownership. Shape hiring and resource plans with engineering leadership, communicate investment tradeoffs to senior leaders, and establish shared metrics for model impact, data coverage, pipeline latency, cost, and delivery against training cutoffs.\nWhat we need to see:\nA BS or MS in Computer Science, Engineering, or a related technical field, or equivalent experience.\n8+ overall years in product management or a related technical role, including 5+ years on data platforms, search/indexing, or ML infrastructure.\n4+ years direct people management experience\nA track record of delivering data systems at scale and improving quality, reliability, processing time, adoption, or cost. Experience building a new platform or taking a technically complex product from concept to production.\nStrong technical understanding of distributed data pipelines, storage, indexing or retrieval, and data processing. Ability to engage in architecture and capacity discussions and make informed product tradeoffs with engineers.\nExperience working closely with research or ML teams to turn evolving needs into datasets or platform capabilities. Good judgment in experiment design, baseline selection, and distinguishing data quality proxies from proven model improvement.\nStrong analytical skills and the ability to inspect data and performance metrics using SQL, Python, or equivalent tools. Comfort making decisions with incomplete information and refining priorities as evidence develops.\nClear written and verbal communication, with proven ability to influence engineering, research, legal, and commercial stakeholders and secure decisions on scope, resources, and investment.\nWays to stand out from the crowd:\nDirect experience with foundation-model training data, large-scale web crawling, source discovery, HTML parsing, or corpus curation.\nExperience evaluating data suppliers, integrating publisher content, defining licensing requirements, or optimizing data acquisition economics.\nBackground with code, mathematical, multilingual, or multimodal datasets, semantic discovery, and quality ranking systems.\nExperience establishing a product function, mentoring product managers, and shaping teams in partnership with engineering leaders.\nFamiliarity with synthetic data, reinforcement-learning environments, or post-training data workflows.\nNVIDIA is widely considered one of the technology world’s most desirable employers. We have some of the world's most forward-thinking and hardworking people on our team. If you're creative and autonomous, 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 240,000 USD - 379,500 USD.You will also be eligible for equity and benefits.\nApplications for this job will be accepted at least until November 1, 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. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.","description_format":"text","description_chars":6450,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Processors, MCUs & AI Chips","Servers & Data Center Hardware","Computer Components","AI Chips & Accelerators"],"lifecycle":[{"event":"open","at":"2026-10-29T00:31:52Z"}],"visa":[],"liveness":{"score":63,"band":"ok","label":"Likely open","p_open":1,"p_active":0.632,"p_room":1,"age_days":1,"expected_fill_days":36,"reasons":["conf:0","stale_co","velocity","win:early","comp:brand"],"computed_at":"2026-10-29T05:49:05Z"},"pay":{"stated_usd_annual":379500,"is_top_pay":true},"html_url":"https://alion.io/job/nvidia-senior-manager-training-data","json_url":"https://alion.io/job/nvidia-senior-manager-training-data.json","meta":{"generated_at":"2026-10-29T06:02:25Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":9200,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-30T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":6},"rest":"https://alion.io/mcp/rest/get_company?id=6"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fnvidia-senior-manager-training-data"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fnvidia-senior-manager-training-data"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fnvidia-senior-manager-training-data"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/nvidia-senior-manager-training-data\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fnvidia-senior-manager-training-data"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3431070}},{"tool":"search_jobs","arguments":{"company":"nvidia.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3431070},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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