Solutions Architect, AI Hyperscalers at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial Intelligence, Cloud ComputingIndustries

Requirements

Minimum of a BS/MS in Computer Science, Electrical Engineering, or equivalent experience
4+ years of engineering experience with a proven track record in AI/ML-focused projects or enterprise-grade solutions
Proven understanding of Linux, including solving, optimization, and customization for AI/ML workloads
Strong understanding of data science and machine learning infrastructure—software and hardware
Professional-level communication skills, including the ability to tailor messages for varying technical audiences and maintain composure in high-pressure situations
Excellent follow-up and interpersonal skills, with a true passion for problem-solving
Proficient in Python, with the ability to develop scripts and build custom tools
Experience with parallel programming or GPU acceleration (e.g., CUDA) is helpful
Shown eagerness to learn and apply new technologies
Ways to stand out (Preferred)
Experience with Chatbots, RAG pipelines, vector databases, and distributed training or inference workloads
Experience or background in HPC (High Performance Computing) environments for AI or ML applications
Familiarity with multi-node GPU clusters and performance tuning for large-scale AI workloads
Experience developing in cloud and/or virtualized environments, containerized solutions, with knowledge of Docker, Kubernetes
Background with common deep learning frameworks such as PyTorch or JAX

Responsibilities

Serve as the main point of contact for NVIDIA products, enabling internet giants and cloud providers to have an innovative AI/ML software infrastructure
Work directly with best-in-class engineering teams to secure design wins, address challenges, bring solutions to production, and support them throughout their lifecycle
Become a trusted advisor to your customer by understanding their environment, constraints, and long-term strategy; translate these insights into product requirements and innovative solutions
Help your customer enhance the value of NVIDIA technology, and provide feedback to NVIDIA for future product improvements
Facilitate the resolution of customer issues, offering timely and proactive communications to mitigate risks
Lead workshops, demos, and proof-of-concepts to showcase NVIDIA’s AI/ML capabilities
Guide customers on standard processes for scalable AI model deployment and inference optimization
Lead software customer technical engagement for AI training, inference and infrastructure being deployed at vast scale
Work across multiple organizations within NVIDIA as well as at the customer to ensure successful and trouble-free deployments

Skills

Key technologies and capabilities for this role

AI/MLSolutions ArchitectureAI TrainingAI InferenceHyperscale InfrastructureCloud Service ProvidersAutomationManagementOptimizationAI ModelsPipelinesProof-of-ConceptsWorkshopsDemosNVIDIA Products

Questions & Answers

Common questions about this position

What education and experience are required for the Solutions Architect role?

A minimum of a BS/MS in Computer Science, Electrical Engineering, or equivalent experience is required, along with 4+ years of engineering experience in AI/ML-focused projects or enterprise-grade solutions.

What technical skills are essential for this position?

Candidates need a proven understanding of Linux for AI/ML workloads, strong knowledge of data science and machine learning infrastructure, and proficiency in Python for developing scripts and tools. Experience with parallel programming or GPU acceleration like CUDA is helpful.

Is this a remote position or does it require office work?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What experience helps candidates stand out for this role?

Experience with Chatbots and RAG pipelines helps candidates stand out from the crowd.

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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