Role at a glance
- Salary
- $184K – $287.5K/yr
- Location
- 2 Locations, Washington, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 6+ years of relevant experience
- Education
- Bachelor’s, Master’s or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience
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Role Summary
The Senior Software Engineer will develop AI software resiliency for NVIDIA AI supercomputers operating at a scale of 100,000+ GPUs. The role focuses on improving the reliability, robustness, and efficiency of AI training and inference workloads through resiliency features, distributed systems engineering, and collaboration across AI software, research, hardware, and software teams.
What You'll Do
- Implement and optimize AI software resiliency features such as fast checkpoint-recovery, error detection, error isolation, and straggler...
- Contribute production-level C++ and Python code for large-scale distributed systems and optimize performance for AI workloads running on...
- Develop error-handling techniques to detect silent data corruption and other failure scenarios, along with monitoring tools for...
- Integrate resiliency features into AI frameworks such as PyTorch and JAX/XLA with senior engineers, AI researchers, and hardware and...
- Develop tests and contribute to CI/CD pipelines to validate the robustness, scalability, and efficiency of resiliency mechanisms.
- Debug and performance-tune large-scale AI workloads in cloud and HPC environments for AI training and inference deployments.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Bachelor’s, Master’s or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience; proficiency in C++ and Python; experience with distributed systems, parallel programming, fault tolerance, AI frameworks, and debugging or profiling tools.
Required
- Bachelor’s, Master’s or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience
- Proficiency in C++ and Python
- Experience writing efficient, high-performance code
- 6+ years of relevant experience
- Strong understanding of distributed systems concepts, parallel programming, and fault tolerance in large-scale computing environments
- Familiarity with AI frameworks such as PyTorch, JAX/XLA, TensorFlow, or similar
- Experience with debugging and profiling tools such as gdb, perf, valgrind, or NVIDIA Nsight
- Excellent problem-solving skills
Preferred
- Hands-on experience in training models or working with model training teams
- Hands-on experience with CUDA, NCCL, or MPI for GPU-accelerated computing, especially at extreme-scale
- Knowledge of checkpointing strategies, error mitigation, or fault-tolerant computing in AI training
- Experience working with large-scale AI clusters, HPC environments, or cloud-based AI workloads
- Strong systems programming skills and experience with low-level performance tuning
Original job description
Content provided by the employer
Original job description
Content provided by the employer
We are now looking for a Senior Software Engineer for AI Resiliency!
At NVIDIA, we are pushing the boundaries of what’s possible in AI. We are currently seeking a Senior Software Engineer to lead the development of AI software resiliency for the most powerful AI supercomputers in the world. As a member of our AI Software Resiliency team, you will play a pivotal role in defining and implementing critical resiliency features for AI supercomputers at a scale of 100,000+ GPUs. Your expertise will be crucial in driving down cluster downtime towards zero, ensuring that our AI systems remain robust and reliable at all times.
What You’ll Be Doing:
Develop AI Software Resiliency Features: Implement and optimize software features that improve AI system reliability at a massive scale, such as fast checkpoint-recovery, error detection, error isolation, and straggler/hang detection.
Hands-On Coding & Optimization: Contribute to large-scale distributed systems with high-quality, production-level C++ and Python code. Enhance performance for AI workloads running on thousands of GPUs.
Fault Tolerance & Debugging: Work on AI system error handling, implementing techniques to detect silent data corruption (SDC) and other failure scenarios. Assist in developing monitoring tools for proactive failure mitigation.
Collaborate Across Teams: Work closely with senior engineers, AI researchers, and hardware/software teams to integrate resiliency features into AI frameworks like PyTorch and JAX/XLA.
Testing & Automation: Develop and implement tests to ensure robustness, scalability, and efficiency of resiliency mechanisms. Contribute to CI/CD pipelines to automate validation of AI workloads.
Support Production Deployments: Assist in debugging and performance tuning large-scale AI workloads in cloud and HPC environments, ensuring seamless operation of AI training and inference workloads.
What We Need to See:
You've achieved a Bachelor’s, Master’s or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
Proficiency in C++ and Python, with experience in writing efficient, high-performance code.
6+ years of relevant experience
Strong understanding of distributed systems concepts, parallel programming, and fault tolerance in large-scale computing environments.
Familiarity with AI frameworks such as PyTorch, JAX/XLA, TensorFlow, or similar.
Experience with debugging and profiling tools (e.g., gdb, perf, valgrind, NVIDIA Nsight).
Excellent problem-solving skills and ability to work in a fast-paced, highly collaborative environment.
Ways to Stand Out From the Crowd:
Hands-on experience in training models or working with model training teams.
Hands-on experience with CUDA, NCCL, or MPI for GPU-accelerated computing, especially at extreme-scale.
Knowledge of checkpointing strategies, error mitigation, or fault-tolerant computing in AI training.
Experience working with large-scale AI clusters, HPC environments, or cloud-based AI workloads.
Strong systems programming skills and experience with low-level performance tuning.
As part of the AI Resiliency team at NVIDIA, you’ll work alongside world-class engineers solving some of the hardest challenges in AI infrastructure. You’ll have the opportunity to contribute directly to making AI training and inference more reliable, scalable, and efficient. If you're passionate about AI, distributed systems, and high-performance computing, 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.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 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.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.