Note: The job is a remote job and is open to candidates in USA. NVIDIA develops GPU-accelerated computing technologies that power AI, data analytics, and scientific and engineering simulations. The Software Engineering Manager will lead a team responsible for expanding and ensuring platform readiness for CUDA Math Libraries, including integration, qualification, compliance, performance validation, defect resolution, and cross-functional roadmap delivery.
Responsibilities
- Lead, mentor, and develop your team
- Own end-to-end platform readiness across Math Libraries for specialized platforms including integration, functional qualification, and compliance
- Collaborate with CI/CD, build, and test infrastructure teams to establish platform-specific qualification and validation pipelines
- Perform 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
- Identify performance targets for new platforms, establish performance testing and fix performance regressions
- Define and deliver to a technical roadmap for platform readiness that scales with the number and complexity of supported platforms
- Work closely within a team of product, engineering, and program managers for dependency coordination across library teams, CUDA, compilers, QA, release processing, and platform organizations
Skills
- PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (or equivalent experience)
- 8+ years of overall experience developing high-performance numerical software
- 3+ years leading and mentoring software engineering teams
- Hands-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
- Strong understanding of fundamental numerical methods and computations in science, engineering, and/or deep learning
- Strong communication, collaboration, and documentation habits
- Experience with, and motivation to adopt and advance, software development practices such as CI/CD systems and project management tools such as JIRA
- Experience with CUDA, GPU-accelerated computing, and parallel programming (e.g. MPI, OpenMP, OpenACC, pthreads)
- Familiarity with math libraries (BLAS, LAPACK, FFT, sparse solvers)
- Proven track record using Agentic AI to boost your efficiency and code quality
- Experience with cross-platform software development and platform bring-up across multiple architectures
- Experience delivering software for safety-critical or embedded environments (e.g., DriveOS, ISO 26262)
Benefits
- Equity
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