7 days ago
Base Salary
$224k - $357k/yr
Responsibilities
- Define manufacturing specification types, schemas, semantics, versioning, and validation methodology derived from system PORs and features.
- Develop production-grade Python pipelines and automated checks for drift across system PORs, ATE, SLT, BLT, and L10+ manufacturing test programs.
- Integrate SMAC workflows with end-to-end program milestones, gates, artifacts, and TPM-driven attestation.
- Build agent-ready tooling with CLIs, MCPs, bug and specification retrieval, human-in-the-loop checkpoints, and evaluation-based CI gates.
- Drive adoption of SMAC methodology and tooling across Post Silicon, Operations, and DFX teams.
- Apply AI to silicon and productization outputs such as speed, power, and binning while preserving reviewable artifacts and manual validation where required.
Requirements
- BS, MS, or equivalent experience in Electrical Engineering, Computer Engineering, Computer Science, or Systems Engineering.
- 8+ years of experience in system software, silicon bring-up, or productization engineering.
- Strong Python and systems skills, including experience shipping production services and data pipelines.
- Deep understanding of system PORs, guard-bands, manufacturing screen specifications, and test insertion constraints.
- Proven cross-organizational influence and experience creating methodologies and workflows adopted by other teams.
- Ability to interpret silicon and productization outputs, including speed, power, and binning, and apply AI with sound engineering judgment.
- Experience building LLM-backed tools for subject matter experts and standing up durable cross-organizational infrastructure is preferred.
Benefits
- Hybrid work arrangement.
- Eligible for equity and benefits.
- Applications will be accepted at least until September 27, 2026.
- This posting is for an existing vacancy.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.