Senior Architect, AI Solutions Engineering at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial Intelligence, SemiconductorsIndustries

Requirements

BS EE/CS or equivalent experience with 10+ years of systems software development with at least 1 year of experience in developing/exploring AI
Development with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Fine-Tuning LLMs, AI Agentic workflows, LangChain, LangGraphs, and Cascading models
Experience in deploying in hybrid, multi-cloud architecture and edge computing
Extensive experience architecting and shipping large-scale distributed software systems
Ability to identify gaps and bottlenecks, and develop solutions to optimize performance
Strong programming and software development skills in JAVA, Python, Shell-script along with good understanding of distributed systems and REST APIs
Experience in working with SQL/NoSQL database systems such as MySQL, Cassandra, MongoDB or Elasticsearch
Excellent knowledge and working experience with Docker containers and Virtual Machines
Good background of Cloud technologies like: OpenStack, Docker, Kubernetes, Chef/Puppet, Hadoop/Ceph/SwiftStack, LXC, Git, Perforce, JFrog, Kafka
Ability to work across organizational boundaries optimally to improve alignment and productivity between teams in a multi-national, multi-time-zone environment
Exceptional technical leadership, communication, organizational, and analytical skills
Passion for solving large and complex problems (e.g., Peta Bytes of fast storage, Million cores, 100,000 builds and 100,000 tests)

Responsibilities

Serve as an Architect developing internal AI systems used by thousands of NVIDIAns globally
Identify gaps and issues and resolve ones better suited for AI solutions versus conventional approaches
Further divide the AI category into 'buy versus build' options by researching available tools in the market
Align with teams across Nvidia to establish overall AI system goals and break them down into specific objectives for each sub-system
Drive, motivate, convince, and mentor sub-system leads to achieve improvements with agility and speed
Identify performance bottlenecks and optimize the speed and cost efficiency of AI development and testing systems
Drive the planning of software/hardware capacity, covering both internal and public cloud, addressing the balance between time and utilization
Introduce technologies enabling massively parallel systems to improve turnaround time by an order of magnitude
Collaborate with AI product vendors to gain deep insights of the AI industry, and share them with leaders and developers internally
Manage the tools NVIDIAns use to deliver solutions quickly, and identify any gaps in these tools
Understand overall movement of data in the entire platform, identifying bottlenecks, defining solutions, developing key pieces, writing APIs, and owning deployment
Collaborate with internal and external development teams to discover opportunities and solve complex problems
Guide engineers in solving complex problems, developing acceptance tests, and reviewing their work and test results

Skills

AI Architecture

Cloud Infrastructure

API Development

Deployment

Deep Learning

NVIDIA GPUs

Linux

Windows

Android

Data Pipelines

Bottleneck Analysis

Technical Leadership

System Architecture

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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