Senior Software Engineer, AI Resiliency at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, TechnologyIndustries

Requirements

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
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)

Responsibilities

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
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
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
Work closely with senior engineers, AI researchers, and hardware/software teams to integrate resiliency features into AI frameworks
Develop and implement tests to ensure robustness, scalability, and efficiency of resiliency mechanisms. Contribute to CI/CD pipelines to automate validation of AI workloads
Assist in debugging and performance tuning large-scale AI workloads in cloud and HPC environments, ensuring seamless operation of AI training and inference workloads

Skills

Key technologies and capabilities for this role

C++PythonPyTorchJAXXLATensorFlowgdbperfvalgrindNVIDIA NsightDistributed SystemsParallel ProgrammingFault Tolerance

Questions & Answers

Common questions about this position

Is this position remote or onsite?

The position is onsite.

What is the salary for this Senior Software Engineer role?

This information is not specified in the job description.

What skills are required for this position?

Required skills include proficiency in C++ and Python, strong understanding of distributed systems concepts, parallel programming, and fault tolerance, familiarity with AI frameworks like PyTorch, JAX/XLA, or TensorFlow, and experience with debugging and profiling tools such as gdb, perf, valgrind, and NVIDIA Nsight.

What kind of team will I be working on?

You will be working on a team focused on AI software resiliency for a scale of 100,000+ GPUs, collaborating closely with senior engineers, AI researchers, and hardware/software teams.

What makes a candidate stand out for this role?

Candidates stand out with hands-on experience in training models or working with model training teams, experience with CUDA, NCCL, or MPI for GPU-accelerated computing at extreme-scale, knowledge of checkpointing strategies, error mitigation, or fault-tolerant computing in AI training, and experience in large-scale computing environments.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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