NVIDIA Logo

NVIDIA

AI Hardware Architect

Reposted 2 Days Ago
Be an Early Applicant
In-Office
Austin, TX, USA
184K-357K Annually
Senior level
In-Office
Austin, TX, USA
184K-357K Annually
Senior level
Architects next-generation GPU and CPU systems, developing microarchitectural solutions for connectivity, coherency, power, security, memory, and protocols. Models performance and power, studies AI workloads, collaborates with software and firmware teams, supports implementation, and helps customers optimize hardware performance. Requires advanced computer or electrical engineering expertise, substantial industry experience, strong coding and algorithmic skills, and understanding of LLMs and chip architecture.
The summary above was generated by AI

NVIDIA is hiring an AI Hardware Architect to analyze and architect the next generation of Artificial Intelligence hardware. We are looking for special individuals with a passion for delivering innovative products. Together, we will build life-changing AI chips and chiplets for the rapidly growing AI infrastructure market. If you have knowledge of computer architecture, microarchitecture, and chip design, and are looking to learn and grow, this is the opportunity you are looking for.  

What you'll be doing: 

  • Work on groundbreaking GPU and CPU systems. Understand them across a range of disciplines and identify areas for improvement.  

  • Study the applications and models running on Nvidia hardware and their architectural implications  

  • Come up with microarchitectural solutions for connectivity, coherency, power management, security, memory management and other SOC level issues.  

  • Understand and help drive implementation of bus protocols, networking protocols, memory access and security solutions across a range of products.  

  • Work with software, firmware, platform and multi-functional teams on system architecture.  

  • Model, analyze, and explain the performance and power advantages of Nvidia solutions.  

  • Guide customers and firmware engineers to extract the most performance from microarchitectural structures.  

What we need to see: 

  • Master's Degree in Computer Engineering or Electrical Engineering (or equivalent experience)

  • 8+ years of relevant industry experience.  

  • Experience building high performance microarchitectural structures. Experience with industry standard bus protocols.  

  • Clear understanding of the performance, power and security implications of microarchitectural features.  

  • Strong interpersonal, communication and teamwork skills.  

  • A drive to continuously learn and expand architectural breadth and depth.  

  • Excellent coding and algorithmic thinking skills. Good understanding of LLMs.  

  • Publications or other evidence of original chip/system architecture work is a plus.  

Join the future of chip building, you will contribute to innovative products with a dedicated team! 

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA Austin, Texas, USA Office

Austin, United States

Similar Jobs

25 Days Ago
In-Office
Austin, TX, USA
200K-300K Annually
Entry level
200K-300K Annually
Entry level
Artificial Intelligence • Hardware • Software • Semiconductor
Designs and evaluates AI model architectures for efficient hardware implementation. The role analyzes transformers and other models, translates computation graphs into hardware dataflows, develops performance and efficiency models, and collaborates across machine learning, software, and hardware teams. Responsibilities include optimizing models for specialized platforms and identifying opportunities for hardware-software co-design in cloud, edge, robotics, autonomous systems, and Physical AI.
Top Skills: Ai AcceleratorsJaxKnowledge DistillationPruningPyTorchQuantizationSparsityTensorFlowTransformers
One Month Ago
Hybrid
Austin, TX, USA
Entry level
Entry level
Artificial Intelligence • Hardware • Machine Learning • Semiconductor
Own the rack-level reference architecture for dense AI compute platforms, covering board and chassis design, interconnect topology, power delivery, thermal management, mechanical constraints, and serviceability. Collaborate with software teams on LLM partitioning and fabric requirements, build quantitative performance and system models, lead trade studies, and carry designs through ODM or OEM production and customer deployment.
Top Skills: 48V Power ConversionActive Optical Cables (Aocs)Advanced PackagingBackplanesBusbarsChipletsCo-Packaged OpticsCold PlatesCooling Distribution Units (Cdus)DacDie-To-Die InterfacesEmc QualificationEthernetHigh-Voltage DcImmersion CoolingLlm Model PartitioningManifoldsOrv3PciePluggable OpticsRasRetimersSerdesTelemetryTwinax
Yesterday
Easy Apply
Remote or Hybrid
United States
Easy Apply
100K-166K Annually
Senior level
100K-166K Annually
Senior level
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Manage enterprise customer implementations of Samsara’s IoT platform, from deployment planning through adoption and value realization. Build launch roadmaps, track implementation and account health, train executives and end users, resolve challenges, and coordinate with Sales, Support, Sales Engineering, Product, and other teams. Mentor Customer Success and Support colleagues while managing multiple customer engagements and strengthening long-term customer relationships.
Top Skills: Enterprise SoftwareIotSaaS

What you need to know about the Austin Tech Scene

Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.

Key Facts About Austin Tech

  • Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
  • Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
  • Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
  • Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
  • Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account