[Remote] Engineering Manager, Math Libraries Consumer and Embedded Platforms

Note: The job is a remote job and is open to candidates in USA. NVIDIA is seeking a Software Engineering Manager to lead platform expansion and readiness for CUDA Math Libraries on new and specialized platforms. The role is responsible for platform integration, functional qualification, compliance, and performance readiness, while coordinating with library, infrastructure, and platform teams.

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

• Eligible for equity
• Benefits
• Hybrid work arrangement

Company Overview

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