{"id":3575706,"url":"https://alion.io/job/nvidia-deep-learning-compiler-verification-engineer","title":"Deep Learning Compiler Verification Engineer","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":83,"open_postings":780,"ghost_share":0.022,"stale_share":0.586,"repost_share":0.041,"time_to_fill_p50_days":38,"computed_at":"2026-11-01T06:10:25Z"}},"role":"Hardware","role_family":"Hardware","seniority":"junior","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","Austin, United States","Hillsboro, United States","Seattle, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":116000,"max":189750,"currency":"USD","period":"year","gross":null,"usd_annual":189750},"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache TVM","optional":false},{"name":"C++","optional":false},{"name":"JAX","optional":false},{"name":"LLVM","optional":false},{"name":"MLIR","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Quantization","optional":false},{"name":"TensorRT","optional":false},{"name":"XLA","optional":false}],"status":"live","first_seen_at":"2026-10-31T21:09:15Z","employer_posted_date":"2026-10-31","last_verified_at":"2026-11-01T18:16:27Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology-and amazing people. 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.\nWe are building the next generation of compiler technologies to accelerate deep learning workloads. We are looking for an engineer to implement compiler verification software & related infrastructure in the AI space. You will be solving critical problems working alongside a diverse set of minds in GPU computing and systems software, doing what you enjoy. If this sounds like a fun challenge, we want to hear from you.\nWhat you'll be doing:\nDevelop and maintain components of systems to reason about correctness in deep learning compilers, across graph transformations, IR lowering, and GPU execution.\nWork with deep learning compiler and architecture teams to analyze and validate optimizations (e.g., graph rewrites in MLIR, fusion passes, mixed-precision transformations), ensuring they preserve semantics and numerical behavior.\nImplement and extend test generation systems that use deep learning solutions and analysis methods to drive in-depth testing. These systems explore the vast combinatorial space of model topologies, precision modes, and hardware targets.\nContribute to improving how we measure functional quality and performance as models, compiler stacks, and hardware continue to evolve.\nWhat we need to see:\nBS, MS or PhD in Computer Science, Computer Engineering, Mathematics, or equivalent experience.\n2+ years of hands-on software engineering experience, with experience in compiler development, deep learning systems, or compiler verification.\nProficiency in Python or C++ and experience with one major DL framework. This could be PyTorch, JAX/XLA, TensorRT, or a similar framework. Experience should involve model execution, graph representation, or runtime behavior.\nStrong problem-solving and debugging skills - ability to reason about model behavior and compiler-generated code, investigate correctness issues, and collaborate with teammates to resolve edge-case failures.\nWays to stand out from the crowd:\nExperience with compiler technologies such as LLVM, MLIR, TVM, or XLA, and familiarity with compiler passes, IR semantics, or correctness testing.\nExposure to formal methods or language specification: type systems, program semantics, or proof-based verification.\nExperience with DL model internals such as quantization, operator fusion, mixed-precision, or graph-level optimization.\nYour base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 116,000 USD - 189,750 USD.You will also be eligible for equity and benefits.\nApplications for this job will be accepted at least until November 4, 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. 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