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.
CI/CD @ 3
Communication @ 6
Data Pipelines @ 3
Debugging @ 6
Distributed Systems @ 5
Go @ 3
JSON @ 3
Linux @ 6
Observability @ 3
Perl @ 3
Python @ 3
- 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.
Details
NVIDIA is building the next generation of production workflow infrastructure for large-scale chip engineering. This platform turns intent, layered configuration, generated files, tool execution, distributed jobs, validation checks, and shared project state into observable, repeatable workflows.
This role is for a systems-minded engineer who may not have prior chip-design or CAD-flow experience, but has strong fundamentals in Linux, automation, configuration systems, scripting, and production infrastructure. You will work alongside senior platform and flow architects to evolve existing Tcl, Make, Perl, Python, YAML, and job-launch infrastructure into a clearer control-plane platform for complex engineering workflows.
Responsibilities
- Build and maintain workflow-platform features across YAML configuration, generated artifacts, Make targets, Perl/Python utilities, Tcl checks, and structured output files.
- Help model workflow stages, inputs, outputs, validation signals, generated files, dependencies, status, and ownership in configuration and manifests.
- Create machine-readable check results, run manifests, provenance records, log summaries, and status outputs that make behavior easier to inspect and debug.
- Strengthen early-failure checks for missing files, stale generated data, invalid configuration, bad environment setup, scheduler issues, and incomplete run state.
- Add and test integrations with distributed job execution, shared compute, filesystem state, data-fidelity tracking, and dependency tracing.
- Work with senior engineers and users to reproduce failures, trace configuration behavior, improve diagnostics, update documentation, and preserve existing workflows.
Requirements
- B.S. or M.S. in Computer Science, Electrical Engineering, Computer Engineering, or equivalent experience.
- 4+ years building automation, developer infrastructure, workflow platforms, distributed systems, test infrastructure, or engineering productivity tools.
- Strong Linux fundamentals, including shell debugging, environment setup, filesystem behavior, process execution, logs, exit codes, and background jobs.
- Practical programming experience in Python, Perl, Go, C++, or similar, with the ability to read and modify Make, YAML, JSON, and shell-based infrastructure.
- Ability to reason carefully about configuration layers, generated files, schemas, validation rules, compatibility, and incremental migration of legacy systems.
- Strong debugging habits, clear written communication, and experience improving production infrastructure without destabilizing active users.
Preferred Qualifications
- Exposure to semiconductor design or EDA workflows, especially RTL, synthesis, place-and-route, timing, signoff, ECO, or handoff flows.
- Background with workflow engines, build systems, CI/CD platforms, job schedulers, deployment automation, data pipelines, or large-scale engineering automation.
- Experience improving legacy Make, Perl, shell, Python, or Tcl systems while preserving existing behavior.
- Experience creating structured logs, JSON/YAML schemas, validation frameworks, provenance tracking, dashboards, or observability tools.
- Background with shared filesystems, partial writes, stale state, locking, reproducibility, generated artifacts, batch jobs, tests, migrations, documentation, or debugging tools.
Benefits
- Competitive salary.
- Generous benefits package.
- Equity eligibility.
- NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.
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