Solutions Architect, Inference Deployments

Reposted 3 Days Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
152K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Lead customer architecture and deployment of scalable AI inference systems across edge and cloud environments. Optimize speech, action, and synthetic data workflows for latency, throughput, memory usage, cost, and quality. Manage production inference configuration, monitoring, capacity planning, testing, releases, and troubleshooting. Evaluate model optimization techniques and create deployment recipes, demos, and enablement materials. Partner with customers, product teams, and engineering to guide technical decisions and accelerate adoption of NVIDIA technologies.
Summary Generated by Built In

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.

Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.


What you'll be doing:

  • Lead architecture discussions with customers and co-design scalable inference systems with product and engineering teams. Define technical direction, integration milestones, and deployment plans across edge and cloud environments.
  • Deploy, test, and profile speech and action models for robotics and automation on edge devices. Optimize latency, throughput, and memory use within device constraints.
  • Lead optimization of synthetic data workflows spanning generation, augmentation, filtering, and data movement. Improve throughput and cost per usable output while preserving data quality.
  • Guide production inference deployments, including configuration, monitoring, capacity planning, performance testing, release validation, and rollback. Resolve complex issues across models, runtimes, and infrastructure.
  • Evaluate model optimization methods, including quantization, kernel selection, and batching. Validate application quality, explain performance tradeoffs, and use findings to inform product and engineering priorities.
  • Drive customer and field enablement through deployment recipes, demos, onboarding materials, and operating guides that help teams adopt and scale NVIDIA technologies.


What we need to see:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
  • 5+ years of professional experience in software or hardware engineering, developer relations, technical partnerships, solutions architecture, or product management, including 3+ years of direct, hands-on experience in AI inference or ML systems.
  • Deep expertise in AI/ML and GPU inference, with a track record of driving product integrations and delivering production systems across edge or cloud environments.
  • Hands-on experience building AI agents and working with Linux systems, containers, and at least one inference runtime or ML framework.
  • Demonstrated expertise in performance profiling and production deployment, including monitoring and troubleshooting. Ability to design repeatable benchmarks that measure performance and application quality.
  • Ability to explain complex technical concepts clearly to technical and non-technical audiences, from engineers to C-level executives.
  • Strong problem-solving skills, intellectual curiosity, and a commitment to learning and helping customers resolve complex technical challenges.
  • A track record of building trusted customer and partner relationships, balancing their needs, and guiding complex product and architecture decisions.


Ways to stand out from the crowd:

  • Technical contributions that demonstrate clear approaches to complex problems and measurable improvements in performance or production reliability.
  • A history of enabling customer adoption, with technical recommendations that influenced product or engineering decisions and delivered production results.
  • Hands-on experience with NVIDIA Jetson, TensorRT Edge-LLM, Nemotron Speech, NVIDIA Riva, ROS 2, or NVIDIA Isaac in voice or robotics deployments.
  • Experience with synthetic data generation or workflow orchestration using NVIDIA Cosmos or comparable tools.
  • Experience with containerized inference, TensorRT-LLM, TensorRT, Triton Inference Server, vLLM, SGLang, or NVIDIA Dynamo.


NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

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:
152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.

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.

Skills Required

  • Bachelor's or Master's degree in Computer Science, Engineering, a related field, or equivalent experience
  • 5+ years of professional experience in software or hardware engineering, developer relations, technical partnerships, solutions architecture, or product management
  • 3+ years of direct, hands-on experience in AI inference or ML systems
  • Deep expertise in AI/ML and GPU inference
  • Experience driving product integrations and delivering production systems across edge or cloud environments
  • Hands-on experience building AI agents
  • Experience working with Linux systems and containers
  • Experience with at least one inference runtime or ML framework
  • Expertise in performance profiling and production deployment, including monitoring and troubleshooting
  • Ability to design repeatable benchmarks measuring performance and application quality
  • Ability to explain complex technical concepts to technical and non-technical audiences
  • Strong problem-solving skills, intellectual curiosity, and commitment to learning and customer support
  • Track record of building trusted customer and partner relationships and guiding complex product and architecture decisions
  • Technical contributions demonstrating measurable improvements in performance or production reliability
  • History of enabling customer adoption and influencing product or engineering decisions through technical recommendations
  • Experience with NVIDIA Jetson, TensorRT Edge-LLM, Nemotron Speech, NVIDIA Riva, ROS 2, or NVIDIA Isaac
  • Experience with synthetic data generation or workflow orchestration using NVIDIA Cosmos or comparable tools
  • Experience with containerized inference, TensorRT-LLM, TensorRT, Triton Inference Server, vLLM, SGLang, or NVIDIA Dynamo

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
  • Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
  • Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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