We are seeking a Sr System Software Engineer to help us build out our scientific computing platform workflows on Cloud. This Cloud based scientific computing cloud platform enables Physics based Numerical Simulation Solvers, AI based Training, Inference and Visualization workflow for physical science and engineering problems.
Those applications include Weather prediction, Climate modeling, Industrial design and Digital twins simulation in various domains e.g Aerospace, Automotive, Sports, Renewable energy, Bio-medical and many more. Are you passionate about solving rewarding problems at scale? Do you enjoy crafting robust, critical services for compute and data intensive workload? If so, you may be a phenomenal fit for our team!
What you’ll be doing:
Design services and take ownership of underlying cloud infrastructure for physics informed and data driven scientific workflows
Design novel algorithms and actively engage with operations to increase overall system performance, it spans across the stack e.g. deep understanding of application code e.g DL Framework, Numerical Solvers, Microservices, APIs and Heterogeneous accelerated computing with CPUs and GPUs.
Design, Build, Deploy and Operate scalable I/O infrastructure for checkpointing, data loading, pre & post processing of data.
Optimize compute, storage and network architecture specific to physics & simulation driven applications.
What we need to see:
BS/MS degree in Computer Science or related areas or equivalent experience.
10+ years experience working on building and operating distributed compute and data intensive platform as a service on cloud
Proven skill in a compiled language (Go, Rust, C++ or otherwise).
Strong foundational knowledge in Cloud Computing e.g “The Datacenter is a Computer” architecture, cloud security architecture, virtualization - CPU, Memory and IO, Resource pooling and elasticity.
Proven skills in Distributed Systems & Parallel Processing e.g System model of distributed computation e.g. topology abstraction, logical time. Synchronization and deadlock detection in distributed systems, Fault Tolerance and Failure Detection, Consensus and Agreement protocols, Parallel algorithms, shared memory and distributed memory architecture, message passing (MPI, NCCL), Cluster scalability and performance.
Hands on Debugging skills with Process, Threads , Deadlock and Synchronization, Scheduling, IPC, Memory management, File system and I/O structure.
Strong Evidence on Algorithmic Thinking & System Design skills e.g Recursion, Graph, Tree, Stack and Queue, Large scale loosely coupled distributed system design and operational experience.
Be self-motivated, have strong interpersonal skills, and be able to work independently with multiple teams with minimal direction.
Ways to stand out from the crowd:
Have built , deployed and operated AI platforms on HPC clusters. Have built, deployed and operated cloud native system including distributed storage, scheduling, and orchestration among compute, storage and network
Configuring and troubleshooting hardware, operating systems, kernel, compilers for maximum performance
Hands on debugging skills to optimize performance of compute, networking and I/O framework. Extensively worked on third party source code for debugging and customization
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.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.#deeplearningSkills Required
- BS or MS degree in Computer Science, a related field, or equivalent experience
- 10+ years of experience building and operating distributed compute and data-intensive platform-as-a-service systems in the cloud
- Proven proficiency in a compiled programming language such as Go, Rust, or C++
- Strong foundational knowledge of cloud computing, cloud security architecture, virtualization, resource pooling, and elasticity
- Proven expertise in distributed systems and parallel processing, including fault tolerance, consensus, parallel algorithms, memory architectures, MPI, and NCCL
- Hands-on debugging skills involving processes, threads, deadlocks, synchronization, scheduling, IPC, memory management, file systems, and I/O
- Strong algorithmic thinking and system design skills, including large-scale distributed system design and operations
- Self-motivated with strong interpersonal skills and ability to work independently across multiple teams
- Experience building, deploying, and operating AI platforms on HPC clusters
- Experience with cloud-native distributed storage, scheduling, and orchestration across compute, storage, and network
- Experience configuring and troubleshooting hardware, operating systems, kernels, and compilers for performance
- Experience debugging and optimizing compute, networking, and I/O frameworks, including third-party source-code customization
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
-
Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
-
Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
.png)
