Jobs at Nuro

The Software Engineer for Performance Tooling and Infrastructure will develop and maintain performance benchmarks, data pipelines, and monitoring systems, ensuring the reliability and scalability of Nuro's testing tools for autonomous vehicles.

Design, build, and operate backend services for ride planning, vehicle matching, and real-time trip execution. Integrate partner APIs, build telemetry pipelines for live vehicle state, and own feature lifecycle from requirements through launch. Ensure reliability and performance of distributed systems used in production on road.

Develop and deploy onboard autonomy software for self-driving vehicles, including real-time decision-making, behavior planning, and performance optimization.

The role involves developing and maintaining performance benchmarking infrastructure, ensuring platform reliability, and designing data pipelines, while collaborating across teams and driving technical vision.

The Sr. Software Engineer will own the perception data infrastructure for autonomous vehicles, dealing with large 3D datasets and ensuring high data quality for ML models. Responsibilities include architecting core data platforms, optimizing real-time data rendering, and collaborating across functions to enhance engineering efficiency.

The Software Engineer will design and implement video streaming solutions, build simulation frameworks, and collaborate on network metrics collection to improve teleoperations.

Design and build safe, auditable agent and autoresearch infrastructure: closed-loop evaluation, isolation and permissioning, experiment orchestration, and large-scale inference/training pipelines. Enable autonomous research loops, evaluator and confidence machinery, and agent runtime features (orchestration, sandboxing, tool frameworks, memory, retrieval). Work end-to-end with engineers to deploy trustworthy LLM-agent capabilities against production systems.

Build and operate large-scale ML training infrastructure: distributed GPU training, multi-cluster scheduling, data pipelines (batch and streaming), ML workflows, observability, reliability, and on-call incident response to keep autonomy model training running efficiently.

Build and operate large-scale ML training infrastructure: distributed GPU training, multi-cluster scheduling, data pipelines (batch & streaming), ML workflows, observability, alerting, and on-call/incident response to ensure reliable, cost-effective model training and releases.

Design, build, and maintain ML infrastructure for model lifecycle: training, optimization, validation, deployment, inference, and observability. Own ML inference and compiler platforms, develop scalable ML pipelines, continuous testing/monitoring, and support deployment to diverse hardware for autonomous vehicles.

Build and maintain core ML infrastructure: design and implement ML training, optimization, validation, and deployment pipelines; operate an in-house ML inference and compiler platform; implement testing, monitoring, and observability for model lifecycles; collaborate with cross-functional teams to deploy optimized models to vehicle hardware.

Design and develop sensor and compute software for autonomous vehicles: device drivers, inter-device protocols, runtime APIs. Ensure reliability via monitoring, automated testing, debugging, vendor collaboration, and cross-functional project leadership.

As Head of Operations, you will lead diverse teams to manage rollouts of autonomous driving technology, ensuring safety, efficiency, and effective operational strategies across multiple geographic locations.

Design, develop, and maintain sensor and compute systems and device drivers for autonomous vehicles. Architect reliable, high-performance onboard software, debug complex real-time systems, lead cross-functional sensor and compute projects, implement automated testing and metrics monitoring, collaborate with vendors, and mentor engineers.

Design and develop sensor and compute systems for autonomous vehicles, build hardware-agnostic device drivers and runtime APIs, debug and optimize real-time systems, deploy reliable software with testing and monitoring, lead cross-functional sensor and compute projects, and mentor junior engineers.

Join Nuro as a Senior Software Engineer in Offboard Infrastructure, focusing on building platforms for data management, simulation, and technical services in autonomy technology.

Serve as the day-to-day HR partner for a large, shift-based operations workforce. Manage high-volume employee relations, safety escalations, onboarding, manager coaching, investigations, documentation, and workforce planning while partnering with cross-functional teams to maintain safety and consistency across sites.

Lead ML efforts for behavior and planning: design, train, and deploy state-of-the-art models (prediction, decision-making, RL/imitation, generative, transformers), own full model lifecycle from data to onboard inference, generalize behavior across geographies and platforms, collaborate cross-functionally, and mentor engineers.

Build and improve ML infrastructure and model pipelines for autonomy: optimize models (quantization, pruning, low precision), maintain and profile GPU ML compilers and runtimes, develop a model compiler framework (FTL), and collaborate with autonomy teams to validate and deploy optimized models to fleet vehicles.

Build and evolve ML infrastructure platform for resource provisioning, workload scheduling, petabyte-scale ETL, feature management, and platform abstractions to support large-scale model development and distributed training.