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# Solutions Architect, Inference Deployments

- **Company:** NVIDIA Corporation
- **Location:** Santa Clara, CA, United States
- **Experience:** Experienced
- **Salary:** $152,000.0 - $241,500.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Engineering, Extract Transform Load (ETL), Linux, Software Deployment, Workflow Management Systems, Cloud Platform System, Performance Testing, Large Language Models, Agentic-AI, Discretization, Isaac Sim, Information Technology, SGLang, Triton Inference Server, Machine Learning Operations, TensorRT, VLLM, Model Inference, NVIDIA Jetson, Data Generation
- **Published:** October 15, 2026
- **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Solutions-Architect--Inference-Deployments_JR2014105

## About the Role

* 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.

## Description

* 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.