Staff Platform Engineer, Design Automation

at Nvidia

USD 196,000-368,000 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 4 API @ 7 Airflow @ 4 CI/CD @ 7 Communication @ 7 Debugging Distributed Systems @ 4 Docker @ 4 ElasticSearch @ 4 GPU Grafana @ 4 HPC @ 4 JavaScript @ 7 Jenkins @ 4 Kafka @ 4 Kubernetes @ 4 LLM Leadership @ 7 Linux @ 7 Networking NoSQL @ 4 Observability @ 7 Python @ 7 RAG @ 4 SQL @ 4 TypeScript @ 7

Details

NVIDIA is seeking a platform engineer to join a small team that builds and operates the software platform used by chip-design teams to launch, monitor, debug, and improve large-scale semiconductor design workflows. The systems coordinate hundreds of thousands of design jobs per day across global datacenters and support more than 1,000 designers working on GPU, CPU, SoC, and networking products.

The role combines distributed systems, developer tooling, workflow orchestration, data infrastructure, applied AI, and semiconductor design methodology. You will help modernize production services, improve the reliability and usability of design-flow infrastructure, and turn design execution data into actionable insights for engineering teams.

Responsibilities

Architect, build, and operate AI-enabled platforms for large-scale VLSI workflows.
Develop reliable backend services, APIs, data models, event-driven systems, and workflow orchestration.
Create web applications for launching, monitoring, debugging, and analyzing design jobs.
Apply LLMs, retrieval-augmented generation (RAG), agents, and automation to accelerate debugging, recommendations, and operational support.
Build telemetry, analytics, and dashboards for workflow health, performance, and quality of results.
Collaborate with EDA, design methodology, and infrastructure teams to improve productivity and tapeout reliability.

Requirements

Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
12 or more years of software engineering experience, including designing and operating distributed production systems.
Strong Python and JavaScript/TypeScript development skills, including experience building backend services, APIs, and modern web applications.
Hands-on experience building applied AI solutions using LLMs, RAG, agents, or related technologies.
Strong understanding of system design, databases, reliability, observability, CI/CD, and Linux operations.
Strong technical communication and multifunctional leadership skills.

Preferred Qualifications

Experience with EDA, VLSI, physical design, static timing analysis, or RTL-to-GDS workflows.
Experience with Temporal, Airflow, Argo, Jenkins, or similar orchestration platforms.
Experience with Docker, Kubernetes, HPC schedulers, or large compute farms.
Experience with SQL/NoSQL databases, Kafka, Elasticsearch, Grafana, or similar platforms.

Compensation and Benefits

Base salary range for Level 5: $196,000–$310,500 USD per year.
Base salary range for Level 6: $232,000–$368,000 USD per year.
Eligible for equity and benefits.
Applications will be accepted at least until August 22, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is an equal opportunity employer committed to an inclusive work environment.