{"id":1427404,"url":"https://alion.io/job/nvidia-engineering-manager-math-libraries-platform-expansion-and-readiness","title":"Engineering Manager, Math Libraries Platform Expansion and Readiness","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":"A","score":89,"open_postings":297,"ghost_share":0.02,"stale_share":0.367,"repost_share":0.04,"time_to_fill_p50_days":28,"computed_at":"2026-10-01T05:45:00Z"}},"role":"Leadership","role_family":"Leadership","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","United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":224000,"max":356500,"currency":"USD","period":"year","gross":null,"usd_annual":356500},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"C++","optional":false},{"name":"CI/CD","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"HPC","optional":false},{"name":"MPI","optional":false},{"name":"OpenMP","optional":false},{"name":"Pthreads","optional":false},{"name":"Python","optional":false},{"name":"C","optional":true}],"status":"live","first_seen_at":"2026-09-28T00:00:00Z","employer_posted_date":"2026-09-28","last_verified_at":"2026-10-01T18:49:34Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"We are looking for a Software Engineering Manager to lead a team responsible for platform expansion & readiness, enabling CUDA Math Libraries on new and specialized platforms. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations using data centers powered by GPUs. NVIDIA’s math libraries are core to the world’s AI infrastructure and must deliver functionality and performance on every target.\nIn this role, you will lead and build a team that provides a single accountable organization for platform integration, functional qualification, compliance, and performance readiness across CUDA Math Libraries, working closely with the core library and devops engineering teams to ensure consistent, high-quality support on every expanding platform. Ideal candidates will be hands-on engineers who also have experience leading software product engineering teams in accelerated computing domains. If this sounds exciting, we would love to meet you!\nWhat You’ll Be Doing:\nLead, mentor, and develop your team.\nOwn end-to-end platform readiness across Math Libraries for specialized platforms including integration, functional qualification, and compliance.\nCollaborate with CI/CD, build, and test infrastructure teams to establish platform-specific qualification and validation pipelines.\nPerform defect triage and isolation of platform-specific versus library-specific problems, fixing bugs to ensure functional correctness, and referring to a library specialist as needed.\nIdentify performance targets for new platforms, establish performance testing and fix performance regressions.\nDefine and deliver to a technical roadmap for platform readiness that scales with the number and complexity of supported platforms.\nWork closely within a team of product, engineering, and program managers for dependency coordination across library teams, CUDA, compilers, QA, release processing, and platform organizations.\nWhat We Need to See:\nPhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (or equivalent experience).\n8+ years of overall experience developing high-performance numerical software.\n3+ years leading and mentoring software engineering teams.\nHands-on experience with object-oriented programming, large system software architecture development, parallel computing, testing, maintenance, and performance optimization of HPC software using C++ and Python.\nStrong understanding of fundamental numerical methods and computations in science, engineering, and/or deep learning.\nStrong communication, collaboration, and documentation habits.\nExperience with, and motivation to adopt and advance, software development practices such as CI/CD systems and project management tools such as JIRA.\nWays to Stand Out from the Crowd:\nExperience with CUDA, GPU-accelerated computing, and parallel programming (e.g. MPI, OpenMP, OpenACC, pthreads).\nFamiliarity with math libraries (BLAS, LAPACK, FFT, sparse solvers).\nProven track record using Agentic AI to boost your efficiency and code quality.\nExperience with cross-platform software development and platform bring-up across multiple architectures.\nExperience delivering software for safety-critical or embedded environments (e.g., DriveOS, ISO 26262).\nYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 3, and 272,000 USD - 431,250 USD for Level 4.\nYou will also be eligible for equity and benefits.\nApplications for this job will be accepted at least until October 2, 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":4263,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","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":"2026-09-29T00:12:53Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":3,"expected_fill_days":28,"reasons":["conf:5","velocity","win:early","comp:brand"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":356500,"is_top_pay":true},"html_url":"https://alion.io/job/nvidia-engineering-manager-math-libraries-platform-expansion-and-readiness","json_url":"https://alion.io/job/nvidia-engineering-manager-math-libraries-platform-expansion-and-readiness.json","meta":{"generated_at":"2026-10-01T21:21:42Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4034,"day_limit":5000,"remaining_today":966,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}