[Remote] Senior Solutions Architect, HPC and AI at NVIDIA

United Kingdom

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, AI, High Performance ComputingIndustries

Requirements

BS, MS, PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or a related engineering field—or equivalent practical experience
8+ years of experience in accelerated computing technologies at cluster scale, ideally including work with NVIDIA platforms
Strong programming skills in at least one of the following languages: C, C++, or Python
Practical experience identifying and resolving bottlenecks in large-scale training workloads or parallel applications
Hands-on experience in profiling and debugging large parallel applications
Solid understanding of CPU and GPU architectures, CUDA, parallel filesystems, and high-speed interconnects
Experienced in working with large compute clusters with an understanding of their internal scheduling and resource management mechanisms (e.g. SLURM or Cloud based clusters)
Proficient knowledge of training pipelines and frameworks, encompassing their internal operations and performance attributes
Ways To Stand Out
Experience in debugging training pipelines running on thousands of GPUs in production environment
Hands-on experience with performance profiling and optimizations using tools like Nsight Systems, Nsight Compute and good understanding of NCCL, MPI and low-level communication libraries
Ability to debug stability issues across the entire stack: parallel application, training frameworks, runtime libraries, schedulers, and hardware
Solid understanding of the internal workings of LLM frameworks such as PyTorch, Megatron-LM, or NeMo, and how they affect compute layers like CPUs, GPUs, network and storage or understanding of inference tools such as vLLM, Dynamo, TensorRT-LLM, RedHat Inference Server or SGLang

Responsibilities

Collaborating with NVIDIA’s training framework developers and product teams to stay ahead of the latest features and help partners to adopt them effectively
Assisting with deployment, debugging, and improving the efficiency of AI workloads on extensive NVIDIA platforms
Benchmarking new framework features, analyzing performance, and sharing actionable insights with both customers and internal teams
Working directly with external customers to solve cluster performance and stability issues, identify bottlenecks, and implement effective solutions
Build expertise and guide customers in scaling workloads efficiently and reliably on the latest generation of NVIDIA GPUs
Contributing to Europe’s Sovereign AI initiative by helping customers implement advanced resiliency features within AI training pipelines

Skills

GPU

HPC

Training Workloads

Inference

NVIDIA

Cluster Scale

Benchmarking

Performance Optimization

Debugging

Resiliency

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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