CloudOps Engineer
Design, build, and automate secure AWS cloud-native infrastructure with Kubernetes and Terraform. Enable dev teams with self-service platforms, CI/CD pipelines, and SRE best practices.
Software Engineer, Performance Tooling and Infrastructure
Builds and maintains performance simulation platform with bench-top rigs, cloud orchestration, and data pipelines to validate autonomy code changes for real-time performance on robot hardware. Requires 3+ years experience in Python/C++, Linux systems, data engineering, with technical leadership.
152k – 228kMountain View, CADevOps / SREOnsite3+ YOE
About the role
Responsibilities
- Develop and maintain job orchestration layer for scheduling, executing, and validating autonomy performance benchmarks across physical bench-top systems, integrated into CI/CD pipelines.
- Build monitoring, alerting, and self-healing automation for the bench fleet; identify capacity bottlenecks, hardware degradation, and single points of failure.
- Design end-to-end data pipelines to capture performance metrics (CPU/GPU utilization, memory bandwidth, E2E latency, scheduling jitter) and surface insights via dashboards and regression detection.
- Collaborate with Data Science on statistical analysis, experimentation methodology, variance analysis, and significance testing for non-deterministic workloads.
- Guide SRE on OS and system-level configuration of bench hardware, including Linux kernel tuning, boot infrastructure, networking, and hardware bring-up.
- Own planning lifecycle for benchmarking fleet across hardware generations; negotiate allocation, model utilization scenarios, and present trade-off recommendations.
- Partner with Hardware Engineering, NPI, SRE, Perception, Behavior, and Data Science teams for self-service infrastructure.
Requirements
- 3+ years of industry software engineering experience.
- Strong proficiency in Python and working proficiency in C++; write clean, testable, well-documented code.
- Experience building data pipelines, ingestion, transformation, storage, and visualization; familiarity with SQL and analytical workflows.
- Deep comfort with Linux systems: kernel configuration, boot debugging, systemd units, bare-metal infrastructure, networking, storage, compute.
- Technical leadership: set vision/roadmap, drive stakeholder alignment, brief senior leadership on trade-offs.
- Use AI as core workflow (e.g., agentic tooling like Claude Code).
Nice-to-Haves
- Performance engineering experience (perf, Perfetto, pprof, eBPF, NVIDIA Nsight Systems, NVIDIA CUPTI).
- Experience in robotics or AV, especially NVIDIA DriveOS.
Compensation
Base pay range: $152,000 - $228,000, depending on experience, qualifications, education, location, skills. Eligible for annual performance bonus, equity, competitive benefits.
Skills
PythonC++KubernetesGCPBigQueryGrafanaLinuxSQLEbpfNvidia Nsight Systems
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