Role at a glance
- Salary
- $152K – $287.5K/yr
- Location
- 2 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 5+ years of work experience
- Education
- Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience
Spotted an issue?
We’ll check it against the original posting.
Role Summary
The Scheduling team within Managed AI Research Superclusters builds infrastructure, platforms, and tools for advanced AI/ML systems. This role designs and implements GPU compute cluster scheduling and orchestration solutions for deep learning, high-performance computing, and other computationally intensive workloads.
What You'll Do
- Design and develop scheduling features and add-on services for GPU compute clusters
- Design and develop batch workload management and orchestration services
- Support staff and end users in resolving batch scheduler issues
- Perform performance analysis and optimization of deep learning workflows
- Develop large-scale automation solutions
- Conduct root cause analysis and suggest corrective action
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Batch scheduling; systems programming in C/C++ and Go; scripting in Python and bash; Linux operating systems, environments and tools; performance analysis and tuning for AI workloads; Docker, Singularity, and Podman; flexibility/adaptability; communication, interpersonal and customer collaboration skills.
Required
- Strong understanding of batch scheduling, preferably with experience in schedulers such as SLURM or K8s batch schedulers (Kueue,...
- Significant experience in systems programming languages such as C/C++ & Go as well as scripting languages such as Python and bash
- Established experience in Linux operating system, environment and tools
- Experience analyzing and tuning performance for a variety of AI workloads
- In-depth understating of container technologies like Docker, Singularity, Podman
- Excellent communication, interpersonal and customer collaboration skills
Preferred
- Knowledge in High-performance computing
- Open Source Software Contribution
- Experience with deep learning frameworks like PyTorch and TensorFlow
- Passionate about SW development processes
Original job description
Content provided by the employer
Original job description
Content provided by the employer
NVIDIA is a pioneer in accelerated computing, known for inventing the GPU and driving breakthroughs in gaming, computer graphics, high-performance computing, and artificial intelligence. Our technology powers everything from generative AI to autonomous systems, and we continue to shape the future of computing through innovation and collaboration. Within this mission, our team, Managed AI Research Superclusters (MARS), builds and scales the infrastructure, platforms, and tools that enable researchers and engineers to develop the next generation of AI/ML systems. By joining us, you’ll help design solutions that power some of the world’s most advanced computing workloads.
As a member of the Scheduling team, you will participate in the design and implementation of groundbreaking GPU compute clusters that run demanding deep learning, high performance computing, and computationally intensive workloads. We seek engineers with deep technical expertise to identify architectural directions and new approaches for AI workload scheduling to serve many simultaneous and large multi-node GPU workloads with complex requirements and dependencies. This role offers you an excellent opportunity to deliver production grade solutions, get hands on with ground-breaking technology, and work closely with technical leaders solving some of the biggest challenges in machine learning, cloud computing, and system co-design.
What you'll be doing:
Design and develop new scheduling features and add-on services to improve GPU compute clusters across many dimensions, such as resource usage fairness, GPU occupancy, GPU waste, application resilience, application performance and power usage.
Design and develop batch workload management and orchestration services
Provide support to staff and end users to resolve batch scheduler issues
Build and improve our ecosystem around GPU-accelerated computing
Performance analysis and optimizations of deep learning workflows
Develop large scale automation solutions
Root cause analysis and suggest corrective action for problems large and small scales
Finding and fixing problems before they occur
What we need to see:
Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience
5+ years of work experience
Strong understanding of batch scheduling, preferably with experience in schedulers such as SLURM or K8s batch schedulers (Kueue, Volcano, etc.)
Significant experience in systems programming languages such as C/C++ & Go as well as scripting languages such as Python and bash
Established experience in Linux operating system, environment and tools
Experience analyzing and tuning performance for a variety of AI workloads
In-depth understating of container technologies like Docker, Singularity, Podman
Flexibility/adaptability for working in a dynamic environment with different frameworks and requirements
Excellent communication, interpersonal and customer collaboration skills
Ways to stand out from the crowd:
Knowledge in High-performance computing
Open Source Software Contribution
Experience with deep learning frameworks like PyTorch and TensorFlow
Passionate about SW development processes
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.