{"id":3695152,"url":"https://alion.io/job/nvidia-software-engineering-intern-2027-2","title":"Software Engineering 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":84,"open_postings":792,"ghost_share":0.023,"stale_share":0.573,"repost_share":0.044,"time_to_fill_p50_days":40,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Backend","role_family":"Backend","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":["Munich, Germany"],"countries":["DE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Git","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TypeScript","optional":false}],"status":"live","first_seen_at":"2026-11-03T17:47:59Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-04T13:34:17Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. Become a Software Engineer Intern at NVIDIA and join the PerfLab team! This exceptional opportunity enables you to work with leading experts and support groundbreaking projects in an inclusive and varied environment. The ideal candidate is a game enthusiast with a good understanding of graphics technologies, would be familiar with NVIDIA products and its characteristics. Experience and passion for PC games is widely welcome.\nWhat you'll be doing:\nIntegrate AI into testing and service workflows to improve troubleshooting, result analysis, and reporting.\nDevelop an MCP tool to analyse service logs.\nCreate an AI Agent to orchestrate troubleshooting, automate triage, and support root cause analysis across multiple services.\nBuild AI-assisted analysis of test results to identify performance regressions, anomalies, and trends across game builds, drivers, and hardware configurations.\nConnect AI analysis with historical results and known issues to provide context and supporting evidence.\nGenerate clear, actionable summaries and integrate their delivery into reports, dashboards, and notifications for our end users.\nCollaborate with testing engineers and customers to evaluate AI-generated findings and improve their accuracy and usefulness.\nImplement observability and feedback loops for safe operation in production.\nPropose new architectures and approaches.\nWhat we need to see:\nCurrently pursuing a Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or related field.\nStrong programming fundamentals, especially in one of: Python (preferred for AI frameworks) or Typescript (for Web development)\nSolid understanding of data structures, algorithms, and API design.\nBasic knowledge of machine learning concepts, especially retrieval-based or agent-based architectures.\nFamiliarity with Git, databases (SQL/NoSQL/Vector) and data pipelines.\nStrong problem-solving skills and eagerness to learn new technologies.\nInterest in applying AI to performance testing, data analysis, and customer-facing workflows.\nStrong collaboration and communication skills, with the ability to learn quickly and work effectively in a dynamic environment.\nWays to stand out from the crowd: Ways to stand out from the crowd:\nStrong experience with Python and Typescript\nExposure to LLM evaluation, structured outputs, or 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