{"id":383372,"url":"https://alion.io/job/nvidia-nvidia-2027-summer-internships-ph-d-engineering","title":"NVIDIA 2027 Summer Internships: Ph.D. Engineering","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":778,"ghost_share":0.026,"stale_share":0.725,"repost_share":0.041,"time_to_fill_p50_days":33,"computed_at":"2026-10-20T05:45:00Z"}},"role":"HR","role_family":"HR","seniority":null,"employment_type":"internship","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":38,"max":94,"currency":"USD","period":"hour","gross":null,"usd_annual":188000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"Digital Twin","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-08-19T00:00:00Z","employer_posted_date":"2026-09-15","last_verified_at":"2026-10-20T15:30:32Z","board_verified":true,"closed_at":null,"days_open":62,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":62},"description":"By submitting your resume, you acknowledge that your Ph.D. Engineering internship application will be processed in accordance with NVIDIA’s Applicant Privacy Policy and you agree to our Terms of Service. We’ll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities.\nNVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society - from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create.\nOur internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading Computer Architecture and Systems teams.We’reseekingstrategic, ambitious, hard-working, collaborative, and creative individuals who are passionate about helping us tackle challenges no one else can solve.\nLearn more about Research at NVIDIA.\nWhat you will be doing:\nDesign and implement novel ideas in GPU and CPU architectures, systems architectures, operating systems, AI systems, and distributed systems that advance computing, graphics, media processing, and related technologies central to NVIDIA's business.\n\nCollaborate with other team members, teams, and/or external researchers.\n\nTransfer your research to product groups to enable new products or types of products. Deliverable results include prototypes, patents, products, and/or publishing original research.\n\nWhat we need to see:\nMust be actively enrolled in a university pursuing a Ph.D. degree in Computer Science, Electrical Engineering, or a related field, for the full duration of the internship; anticipated graduation date (month and year) must be clearly indicated on a resume or CV to be considered.\n\nDepending on the internship, prior experience or knowledge requirements couldinclude the following programming skills and technologies: C, C++, Python,CUDA\n\nStrong background in research with publications at top conferences.\n\nExcellent communication and collaboration skills.\n\nPotential internships require research experience in at least one of the following areas:\nChip-level and System-level Architecture\n\nGPU and Multi-GPU ArchitectureScalable memory systems and new memory technologies\nScalable on-chip and off-chip interconnects\nChip-level and system-level scheduling\nPower, performance, and energy-efficiency in large-scale systems\nSpecialized accelerators for workloads like AI algorithms, crypto algorithms, databases, etc.\nHardware-software co-design\nSystems for AI/ML\n\nSystems Infrastructure for large LLM training and inference\nSystems/AI algorithms codesign (e.g., for sparsity)\nAI/ML for systems (hardware design, code optimization, etc.)\nML for EDA\nProgramming Systems\n\nGPU-accelerated algorithms\nLanguages and programming models for parallel computing\nOptimizing compilers and AI-based performance assistants\nDistributed runtime systems\nSystems software and operating system interfaces\nOptimizing GPU-accelerated workloads\nCompilers and code verification\nHigh-Performance Networking and Interconnects\n\nLarge-scale GPU networking\nTopologies, routing, and congestion control\nNetworking techniques at the intersection of scale-out and scale-up\nVLSI and Electronic Design Automation (EDA)\n\nGPU Accelerated EDA\nClick here to learn more about NVIDIA, our early talent programs, benefits offered to students and other helpful student resources related to our latest technologies and endeavors.\nOur internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 38 USD - 94 USD.\nYou will also be eligible for Intern benefits.\nApplications are accepted on an ongoing basis.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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