System Software Engineer, Distributed Systems (Equity)

NVIDIA; Santa Clara (CA); On-site; USD 152,000 - 288,000; Full time

Job summary

NVIDIA’s VLSI Productivity and Infrastructure team is seeking a versatile systems engineer for distributed, low-abstraction Linux environments and long-running workflows. You’ll own userspace software that coordinates state, concurrency, and reliability at scale, with a focus on Go and Python in large codebases.

Join an environment that values practical engineering, incremental modernization, strong observability, and collaboration with fellow engineers to deliver durable production systems on

Qualifications

• B.S. CS/EE (or equivalent experience).
• 5+ years developing and operating production software in Go and/or Python, ideally in large codebases.
• Strong Linux fundamentals: processes, filesystems, permissions, synchronization/locks, concurrency, and debugging.
• Solid distributed-systems thinking: failures, retries/timeouts, backoff, idempotency, and operational rigor.
• Experience building long-runtime automation or services on shared compute clusters (batch schedulers, build systems).
• Ability to translate ambitious, high-level goals into a safe delivery plan (instrumentation, staged rollout, measurable outcomes).

Responsibilities

• Design, build, and deliver core components of our next-generation productivity platforms.
• Develop reliable userspace infrastructure for long-running engineering workflows at scale on bare-metal Linux hosts.
• Build state coordination over NFS (atomicity, idempotency/dedup, partial-write recovery, without privileged ops)
• Build and improve orchestration around IBM LSF (submission/tracking, retries/cancel, log capture, fairness/backpressure)
• Convert legacy codebases into modern powerhouses using incremental migration techniques (e.g., Perl to Go), with stage gates, parity strategies, and strong observability
• Debug and improve performance and reliability across Linux and Kubernetes, including operational tooling
• Collaborate with engineering users to turn ambiguous workflows into durable production systems

Skills

Go

Python

Linux fundamentals

Distributed systems

Batch scheduling

Education

B.S. CS/EE or equivalent experience

Tools

Kubernetes

Job description

NVIDIA’s VLSI Productivity and Infrastructure team is seeking a versatile systems engineer for distributed, low-abstraction Linux environments and long-running workflows. You’ll own userspace software that coordinates state, concurrency, and reliability at scale, with a focus on Go and Python in large codebases.

Join an environment that values practical engineering, incremental modernization, strong observability, and collaboration with fellow engineers to deliver durable production systems on