Full-Time

Solutions Architect

AI Hyperscalers

Confirmed live in the last 24 hours

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI computing solutions

Compensation Overview

$148k - $287.5k/yr

+ Equity

Senior

Company Historically Provides H1B Sponsorship

Santa Clara, CA, USA

In Person

Category
Solution Engineering
Sales & Solution Engineering
Required Skills
Python
Data Science
CUDA
Machine Learning
Linux/Unix
Requirements
  • Minimum of a BS/MS in Computer Science, Electrical Engineering, or equivalent experience.
  • At least 5+ 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.
Responsibilities
  • As a key technical member of a focused account team, you will 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.
Desired Qualifications
  • 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.
  • Experience with common deep learning frameworks such as PyTorch or JAX.

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 main products are GPUs that enhance gaming experiences and support professional applications, along with AI and high-performance computing platforms tailored for developers and data scientists. NVIDIA stands out from competitors by offering a combination of hardware and software solutions, including cloud-based services like NVIDIA CloudXR and NGC, which enable scalable applications in AI and machine learning. The company's goal is to drive innovation in technology and provide advanced solutions that cater to a wide range of clients, from gamers to enterprises.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

Simplify Jobs

Simplify's Take

What believers are saying

  • Acquisition of Lepton AI enhances NVIDIA's AI infrastructure and cloud solutions.
  • Collaborations with Utilidata position NVIDIA as a leader in smart grid solutions.
  • Investment in Skild AI expands NVIDIA's reach in the robotics systems market.

What critics are saying

  • Emerging competition from startups like Emerald AI challenges NVIDIA's market dominance.
  • Integration challenges from acquisitions like CentML and Lepton AI pose potential risks.
  • Financial risks arise from investments in startups like Skild AI and AI21.

What makes NVIDIA unique

  • NVIDIA leads in AI and HPC with cutting-edge GPU and SoC technologies.
  • The company excels in AI model optimization through strategic acquisitions like CentML.
  • NVIDIA's cloud services, like CloudXR, offer scalable solutions for diverse applications.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

1%

1 year growth

0%

2 year growth

0%
Axios
Jul 1st, 2025
Nvidia stakes new startup that flips script on data center power

Emerald AI is emerging from stealth as the AI surge risks straining grids, and hyperscalers are limited by power availability.

Yahoo Finance
Jul 1st, 2025
xAI raises $10B in debt and equity

Elon Musk's AI company, xAI, has raised $5 billion in debt and $5 billion in equity, Morgan Stanley said on Monday.

Yahoo Finance
Jun 27th, 2025
Nvidia acquires Canadian AI startup CentML - The Logic

Investing.com -- Nvidia (NASDAQ:NVDA) has acquired Canadian AI startup CentML, bringing the company’s leadership and staff into its ranks, according to The Logic, citing sources familiar with the matter.

ITjuzi
Jun 12th, 2025
Skild AI Secures $200M in Funding

Skild AI, a robotics systems developer, has secured a $200 million Series B funding round, bringing its valuation to approximately $4.5 billion. The round was led by Japan's SoftBank Group, which contributed $100 million. Other investors include NVIDIA and Samsung Electronics.

Dealroom
Jun 2nd, 2025
Nvidia company information, funding & investors

Nvidia, designing and manufacturing high-performance gpus, ai platforms, and software solutions for gaming, professional visualization, data centers, and autonomous vehicles. Here you'll find information about their funding, investors and team.