Develop and support NVIDIA CUDA Math Libraries across emerging and specialized platforms. Responsibilities include platform integration, functional qualification, defect triage, bug fixing, performance benchmarking, regression resolution, and building CI/CD qualification pipelines. The role requires high-performance numerical software development using C++ and Python, parallel computing, numerical methods, and software architecture, with preferred experience in CUDA, GPU computing, math libraries, cross-platform development, and embedded or safety-critical systems.
We are looking for a Senior Software Engineer to join our team enabling CUDA Math Libraries on new and specialized platforms. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations using data centers powered by GPUs. NVIDIA’s math libraries are core to global AI infrastructure and must deliver functionality and performance on every target.
In this role, you will enable NVIDIA’s CUDA Math Libraries on a wide variety of emerging platforms, including integration, functional qualification, compliance, and performance readiness, working closely with the core library and devops engineering teams to ensure consistent, high-quality support on every expanding platform. Ideal candidates will have experience in scientific and numerical computing libraries, GPU kernel development, and parallel programming. This is your opportunity to join an organization that is on the forefront of unlocking application performance in the AI era! We would love for you to bring your talent to the team.
What You’ll Be Doing:
- Ensure platform readiness across Math Libraries (including cuBLAS, cuSPARSE, cuSOLVER, cuFFT, and others) for new and specialized platforms.
- 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.
- Collaborate with CI/CD, build, and test infrastructure teams to establish platform-specific qualification and validation pipelines.
What We Need to See:
- PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (or equivalent experience).
- 5+ years of overall experience in developing high-performance numerical software.
- 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 software development practices, such as CI/CD systems, and project management tools such as JIRA.
Ways to Stand Out from the Crowd:
- 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.
- Background with delivering software for safety-critical or embedded environments (e.g., DriveOS, ISO 26262).
#LI-Hybrid
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Similar Jobs
Fintech • Information Technology • Insurance • Financial Services • Big Data Analytics
Leads a team managing ADA and PWFA accommodation claims, ensuring accurate, timely, compliant claim adjudication and strong customer service. Responsibilities include coaching employees, managing performance and workloads, reviewing claim files and calls, identifying process improvements, administering concurrent disability and leave claims, mitigating risk, and communicating operational updates. The role requires disability or absence management expertise, sound judgment, knowledge of applicable regulations, and effective stakeholder collaboration.
Top Skills:
Microsoft Office Suite
Fintech • Information Technology • Insurance • Financial Services • Big Data Analytics
Processes long-term care reimbursement claims by interpreting policy provisions, reviewing documentation, calculating payments and overpayments, and identifying potential fraud, waste, and abuse indicators. The role obtains missing information from providers, collaborates with internal teams, and meets quality, accuracy, productivity, and timeliness standards. It is primarily virtual with a required monthly office visit.
Top Skills:
Ai-Powered ToolsComputer-Based Claims Processing SystemsExcelMicrosoft WordTlc Claims System
Artificial Intelligence • Cloud • Payments • Software • Business Intelligence • Generative AI • Automation
Manages strategic insurance industry alliance partners, driving revenue through partner enablement, joint business plans, go-to-market strategies, training, and product education. Tracks partner KPIs and pipeline performance, collaborates with sales, marketing, customer experience, and product teams, represents the company at industry events, and negotiates partner contracts and incentives.
Top Skills:
AICloud SoftwareCrm SystemsSaaS
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
