Senior Manufacturing and System Co-Design Workflow Engineer

Job Title

Senior Manufacturing and System Co-Design Workflow Engineer

Role Summary

Lead the methodology and infrastructure that keeps system intent and manufacturing specifications aligned across NVIDIA GPU, SoC, and CPU programs. The role sits on the System–Manufacturing Architecture (SMAC) team and focuses on workflow design, automated checks, and integration with program milestones to prevent specification drift.

Experience Level

Senior — requires substantial experience; role requests 8+ years of relevant experience.

Responsibilities

The role owns end-to-end workflow methodology, production tooling, and cross-organization adoption to ensure specification alignment from pre-silicon POR through production release.

• Define manufacturing specification types, schemas, semantics, and lifecycle/versioning rules derived from system PORs and features.
• Design and implement production-grade Python pipelines and automated checks to detect spec drift between system POR and manufacturing test programs (ATE, SLT, BLT, L10+).
• Integrate SMAC outputs into program spine, milestones, gates, and TPM attestation processes to require proof of alignment at key stages.
• Develop agent-ready tooling and CI infrastructure (CLIs, MCPs, bug/spec retrieval, human checkpoints, evaluation-based CI) compatible with real silicon workflows.
• Drive cross-organizational adoption across Post-Silicon, Operations, and DFX teams, and shepherd workflows from prototype to relied-upon infrastructure.

Requirements

Key must-have skills and experience; candidates should demonstrate production delivery and cross-org influence.

• 8+ years in system software, silicon bring-up, or productization engineering working with real silicon programs.
• Strong Python and systems engineering skills; experience shipping production services and data pipelines.
• Deep understanding of spec ecosystem: system POR, guard-bands, manufacturing screen specs, and test insertion constraints.
• Proven track record of influencing and driving methodology adoption across multiple organizations.
• Ability to interpret silicon and productization outputs (speed, power, binning) and apply AI/automation with appropriate human-review checkpoints.
• Nice-to-have: experience building LLM-backed tools, and demonstrated success delivering cross-org workflows that achieved sustained adoption.

Education Requirements

BS or MS (or equivalent practical experience) in Electrical Engineering, Computer Engineering, Computer Science, or Systems Engineering. The posting explicitly allows equivalent experience in lieu of a degree.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.