Job Description
At Nuro, your base pay is one part of your total compensation package.
Key Responsibilities
- Nuro leverages many different bench-top systems to evaluate and regression test different aspects of the software and hardware integration layer. This performance simulation platform includes systems
- At Nuro, every autonomy code change, from ML model updates to radius of map around the robot to number of evaluated trajectories, must be validated for real-time performance on actual robot compute hardware before it reaches the road. You will own the infrastructure that makes this possible.
- Our Performance Simulation Platform is a hybrid benchmarking system: physical bench-top rigs running production robot compute (NVIDIA Thor platform), orchestrated by cloud-native infrastructure (Kubernetes, GCP), automated data pipelines feeding performance metrics into BigQuery and Grafana, pre/post simulation magic, custom tracing and profiling tools, and much much more.
- Engineers across the company rely on this platform daily to answer questions like:
- How will my new ML model affect contention on the GPU?
- How does a new data format impact onboard logging rate or network contention as more data might be flowing from through the system?
- How much memory should be allocated for this new module, and how does it fit into the overall system budget?
- You'll be responsible for development, integration, and the evolution of this platform — from the bare-metal OS and networking layer through the job orchestration and CI/CD integration up to the data analysis and visualization layer. This is a high-ownership, high-autonomy role on a small team where your work directly gates the release velocity of the entire autonomy stack. You'll be the technical DRI for the platform — setting the roadmap, making architectural calls, representing the platform's needs to the leadership team, and ensuring the system scales through multiple hardware generations.
Requirements
- Experience: ~1+ years of industry software engineering experience.
- Software Engineering: Strong proficiency in Python and working proficiency in C++. You write clean, testable, well-documented code and care about long-term maintainability.
- Data Engineering: Experience building data pipelines, ingestion, transformation, storage, and visualization. Familiarity with SQL and analytical workflows.
- Systems & Infrastructure: Deep comfort with Linux systems — you've configured kernels, debugged boot issues, written systemd units, or managed bare-metal infrastructure. You understand networking, storage, and compute at a level beyond "it just works."
- Technical Leadership: Experience setting technical vision and roadmap for a project or platform, driving alignment across multiple stakeholders. You've independently identified the cross-functional partners needed to unblock and deliver, and you've briefed senior engineering leadership on trade-offs and recommendations.
- AI-Native: You treat AI as a core part of your engineering workflow, not an occasional shortcut — you use agentic tooling (e.g., Claude Code) across the development lifecycle and you understand the boundaries of when AI output demands extra scrutiny versus when it accelerates you.
- Bias for Action: Comfortable operating in ambiguous, fast-moving environments where you need to balance long-term architecture with short-term delivery.
Ready to Apply?
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