Software Engineering Manager

We are seeking a Software Engineering Manager to lead a team focused on platform expansion and readiness, enabling CUDA Math Libraries on new and specialized platforms.

In this role, you will lead and build a team responsible for platform integration, functional qualification, compliance, and performance readiness across CUDA Math Libraries. You will work closely with core library and devops engineering teams to ensure consistent, high-quality support on every expanding platform.

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 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

Requirements:

• PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or a related 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 like JIRA

Preferred Qualifications:

• 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 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)