Scientific Software Engineers

Reposted 3 Days Ago
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Santa Clara, CA, USA
In-Office
180K-339K Annually
Senior level
Artificial Intelligence • HR Tech • Information Technology • Social Impact
The Role
The role involves designing, building, and operating microservices and APIs for scientific computing on the Nvidia DGX cloud, optimizing data-intensive applications, and ensuring systems performance across various domains.
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Company Description

Jobs for Humanity is collaborating with Upwardly Global and with Nvidia to build an inclusive and just employment ecosystem. We support individuals coming from all walks of life.
Company Name: Nvidia

Job Description

Senior System Software Engineer - Scientific Computing PaaS
locations: US, CA, Santa Clara; US, Remote
time type: Full time
posted on: Posted Today
job requisition id: JR1979896
We are seeking a Sr System Software Engineer to help us build out our scientific computing platform on Nvidia DGX Cloud. We are building a cloud-based accelerated scientific computing platform as a service on the Nvidia DGX cloud. This DGX 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 workloads? If so, you may be a phenomenal fit for our team!
What you'll be doing:
Design, Build, Deploy, and Operate Cloud-native microservices and APIs for scientific computing workload on DGX cloud.
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 of 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, kernels, 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!
The base salary range is 180,000 USD - 339,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. You will also be eligible for equity and benefits.
NVIDIA accepts applications on an ongoing basis. NVIDIA is committed to fostering a diverse 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.
#deeplearning

Skills Required

  • BS/MS degree in Computer Science or related areas
  • 10+ years experience in distributed compute platforms
  • Proven skill in a compiled language (Go, Rust, C++)
  • Strong knowledge in Cloud Computing architecture
  • Proven skills in Distributed Systems & Parallel Processing
  • Hands-on Debugging skills with Process, Threads, and Memory management
  • Strong evidence of Algorithmic Thinking & System Design skills
Am I A Good Fit?
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The Company
100 Employees
Year Founded: 2020

What We Do

Jobs for Humanity connects historically underrepresented talent, including persons with disabilities, refugees, and immigrants, with welcoming employers. They leverage AI to streamline the hiring process, aiming to create a fairer future for all.

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