Senior Performance Analysis Engineer at NVIDIA

Zurich, Zurich, Switzerland

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

B.Sc in Computer Science or Software Engineering or equivalent experience
5+ years of experience with high-performance Networking (RDMA, MPI, NCCL, Congestion Control Algorithms)
Demonstrated Performance Analysis skills and methodologies
Experience with NVIDIA GPUs, CUDA library, deep learning frameworks like TensorFlow or PyTorch, combined with expertise in networking collective communication libraries (such as NCCL) and protocols (such as RoCE and RDMA)
Fast and self-learning capabilities with strong analytical and problem-solving skills
Programming Languages: Python, Bash and C languages
Experience with Linux OS distros
Great teammate with good communication and interpersonal skills

Responsibilities

Exploring and researching AI workloads and DL models specifically tailored for large-scale deep learning LLM training on NVIDIA supercomputers and distributed systems focusing on high-performance networking and Nvidia Collective Communications Library (NCCL)
Benchmarking, Profiling, and Analyzing the performance to find bottlenecks and identify areas of improvement and optimizations, with a strong emphasis on networking aspects
Implementing performance analysis tools
Collaborating with many teams from hardware to software to provide performance analysis insights
Defining performance test planning, setting performance expectations for new technologies and solutions, and working to reach the performance targets limits

Skills

Key technologies and capabilities for this role

HPCAI NetworkingNCCLGPUCPUDistributed Deep LearningLLM TrainingBenchmarkingProfilingPerformance AnalysisCollectives Communication

Questions & Answers

Common questions about this position

What salary is offered for the Senior Performance Analysis Engineer role?

This information is not specified in the job description.

Is this position remote or does it require working from an office?

This information is not specified in the job description.

What skills and experience are required for this role?

Required qualifications include a B.Sc in Computer Science or equivalent, 5+ years with high-performance Networking (RDMA, MPI, NCCL, Congestion Control), performance analysis skills, experience with NVIDIA GPUs, CUDA, deep learning frameworks like TensorFlow or PyTorch, networking libraries like NCCL, programming in Python, Bash, C, Linux OS, and strong analytical and teamwork skills.

What is the company culture like at NVIDIA for this team?

NVIDIA emphasizes an exciting environment for innovation in AI and visual computing, with a collaborative approach across hardware and software teams, valuing great teammates with good communication and interpersonal skills.

What makes a candidate stand out for this Senior Performance Analysis Engineer position?

Candidates stand out with in-depth knowledge of AI workloads and benchmarking for distributed LLM training, knowledge in CUDA and NCCL libraries, congestion control algorithms, and in-depth system knowledge of Intel/AMD/ARM CPUs, NVIDIA GPUs, and HCAs.

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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