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.
About the job
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
Python, C++, Kubernetes, GCP, BigQuery, Grafana, Linux, SQL, Ebpf, Nvidia Nsight Systems
Similar jobs
DevOps / SRE jobs
Cloudflare
Austin, TXBuild and operate a highly available, multi-region PostgreSQL platform, developing automation, monitoring, disaster recovery, and performance tooling. Requires experience with large-scale PostgreSQL clusters, infrastructure as code, scripting, containers, and observability.
Fluidstack
New York, NYLeads on-site deployment of data center physical infrastructure, managing contractors, performing QA/QC on fiber optics and cabling, and ensuring compliance with standards. Requires 5+ years experience, SME-level fiber optic expertise, bachelor's degree, and 40% travel readiness.
Trexquant
New York, NY
The Python Engineer will improve and operate trading systems, support integrations with asset classes and prime brokers, and handle monitoring, incidents, and performance optimization. The role requires 3+ years of experience, strong Python and Linux skills, and familiarity with market data and order-entry systems.
Teleport
United States
Build IT workflow automation and security tooling using Go, Temporal, Kubernetes, Terraform, and shell scripting. The role also supports internal IT systems and integrations across endpoint management, identity, access, and security administration.
SimplePractice
United States
The DevOps Engineer will build and operate reliable infrastructure, deployment workflows, and observability for data pipelines and AI/ML systems. The role requires at least three years of DevOps, SRE, or infrastructure experience plus strong cloud, Terraform, containerization, and MLOps expertise.