AI Autonomous Systems Engineer Jobs

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The role involves defining and building next-generation CPU networking architecture for datacenter and emerging robotics/automotive applications, contributing to current datacenter networking efforts, and helping to specify future medium- to low-power robotics/automotive devices for AI/ML compute and sensor ingestion. The engineer will work at the intersection of NoC, performance modeling, and RTL design to guide architectural decisions, collaborate across hardware, software, and systems teams to define and refine networking requirements, and help drive forward next-generation CPU networking architecture specifically for AI/ML workloads.

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Deploy Sunrise robotic systems in live manufacturing environments ensuring successful customer go-lives. Translate real-world production constraints into structured feedback that improves product capabilities and deployment workflows. Identify opportunities to reduce non-recurring engineering effort and improve delivery scalability. Contribute to the refinement of Sunrise's tools, processes, and system architecture to enable repeatable deployments. Collaborate closely with AI, robotics, product, and commercial teams to align customer needs with product evolution. Support pilot launches and early deployments ensuring systems meet defined performance and operational success criteria. Act as a technical partner to customers during integration, building trust and ensuring long-term success. Provide technical support to customers during troubleshooting and maintenance of deployed robotic systems. Investigate and respond to operational incidents or anomalies in robotic systems ensuring timely resolution and system reliability.

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Contribute to defining and building next-generation CPU networking architecture for datacenter and emerging robotics/automotive applications, including current datacenter networking and specifying future medium- to low-power robotics/automotive devices for AI/ML compute and sensor ingest. Work at the intersection of Network on Chip (NoC), performance modeling, and RTL design to guide architectural decisions. Collaborate across hardware, software, and systems teams to define and refine networking requirements. Help drive the advancement of next-generation CPU networking architecture for AI/ML workloads.

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Contribute to the development of next-generation CPU networking architecture for both datacenter and emerging robotics/automotive applications, including current datacenter networking efforts and early-stage automotive/robotics device specifications. Work at the intersection of Network-on-Chip (NoC), performance modeling, and RTL design to guide architectural decisions. Collaborate across hardware, software, and systems teams to define and refine networking requirements. Drive forward next-generation CPU networking architecture for AI/ML workloads, and take an early-stage concept from seeding and specification through to project initiation in automotive/robotics networking.

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The role involves defining and building next-generation CPU networking architecture for both datacenter and emerging robotics/automotive applications. The engineer will contribute to current datacenter networking efforts while also helping to seed and specify future medium- to low-power robotics/automotive devices for AI/ML compute and sensor ingest. They will work at the intersection of NoC, performance modeling, and RTL design to guide architectural decisions and collaborate across hardware, software, and systems teams to define and refine networking requirements. The position includes driving the development of next-generation CPU networking architecture for AI/ML workloads and taking early-stage automotive/robotics networking concepts from seeding and specification through to project initiation.

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As an Automotive and Robotics SoC Architect, you will define scalable, top-down system architectures that unify CPU and AI technologies for next-generation automotive applications. This role involves shaping the architectural direction of the automotive and robotics portfolio to ensure products meet the highest expectations for performance, safety, reliability, and security. It requires strong technical leadership, systems thinking, and cross-functional collaboration to deliver world-class automotive solutions. The position is remote and based out of North America.

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As a Senior Autonomy Systems Test Engineer, you will oversee the development of extensive test plans, develop standardized simulated test design tooling processes to execute many different scenarios, validate end-to-end behaviors, and create triage pipelines for analyzing issues observed during offline and on-vehicle testing. You will participate regularly in in-vehicle testing missions to observe new features in real-world conditions, help triage and root cause issues found during testing, analyze test results to ensure no regression in existing functionality, and update testing processes to enable scalable QA for future milestones. Additionally, you will create test strategies and plans for self-driving behavior features, identify, track, report, and resolve testing issues with cross-functional software development teams, propose, prototype, and validate new automated testing methodologies for the AI stack, design, develop, and execute synthetic and log-based test scenarios on an in-house simulation framework, and compile triage strategies and results from different QA validation platforms and pipelines.

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As an Automotive and Robotics SoC Architect, you will define scalable, top-down system architectures that unify CPU and AI technologies for next-generation automotive applications. This role involves shaping the architectural direction of the automotive and robotics portfolio to ensure products meet the industry's high standards for performance, safety, reliability, and security. The position requires strong technical leadership, systems thinking, and cross-functional collaboration to deliver world-class automotive solutions.

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The position involves participating in an internship for Autonomous Driving Group where the candidate will engage in research and development aiming to connect research results to actual mass-production autonomous driving systems. Responsibilities include End-to-End design, implementation, and validation of core autonomous driving system technologies; designing and validating algorithms and models based on real vehicle data; performance analysis and improvement through simulation and real-road experiments; implementing research outcomes into applicable system forms; and close collaboration with production teams within the AD Group to solve problems. Depending on the specialization, tasks may include implementing perception and prediction ML models, preprocessing and analyzing driving data, evaluating model performance and analyzing results, object-level fusion and tracking using sensor data, real-time fusion logic improvement, SLAM and localization algorithm development, integration and debugging of vehicle software under Linux environment, designing data pipelines for autonomous driving data collection and analysis, vision-language-action model research, and building learning and evaluation pipelines with cross-department collaboration.

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Design algorithms that decompose high-level missions into structured, solvable guidance tasks for autonomous robots. Develop and optimize mission and path-planning frameworks for autonomous systems. Build scalable backend integrations for mission guidance and execution. Run simulations and validation campaigns to assess autonomy consistency across diverse mission types. Partner with AI/ML, backend, and product teams to ensure algorithms are efficient, testable, and deployable in real-time environment.