Top Engineering Jobs

Conduct original robotics research across learning, perception, planning, control, safety, systems, and mechatronics. Develop and evaluate methods on real robotic platforms and simulations, integrate multidisciplinary capabilities into intelligent systems, publish research, identify system-level bottlenecks, and influence the technical roadmap for future robotics compute and software platforms.

Design and integrate complex compute subsystems and SoCs, including PCIe, DDR, HBM, UCIe, and Ethernet IP. Develop micro-architecture specifications and RTL, perform design checks, debug issues, and collaborate with verification, performance, backend implementation, and project management teams. Support floor planning, timing closure, design methodologies, and team development while guiding other engineers.

Develop and deploy Raven, a C++ dynamic random test generator for Arm CPU verification. Responsibilities include implementing verification functionality, creating test templates for architectural and microarchitectural features, debugging user and QA issues, collaborating with CPU verification engineers, and applying computer architecture specifications. The role requires strong C++ development, assembly programming, computer architecture knowledge, and familiarity with CPU verification environments.

Develop system-level stress workloads and validation tests for Arm SoC processors in Linux and bare-metal environments. Characterize silicon, debug system and silicon issues, create test plans, and perform root-cause analysis using laboratory and debugging equipment. The role requires pre- and post-silicon validation experience, software engineering skills in C/C++, ARM assembly, Python, and scripting, plus knowledge of power, performance, and hardware interfaces.

Develop reusable Python-based software infrastructure for post-silicon validation and characterization of Arm SoCs. Build automation, frameworks, APIs, and CI or regression infrastructure for workloads, hardware controls, instrumentation, test execution, and data collection. Collaborate with firmware, validation, systems, and infrastructure teams to debug complex hardware-software interactions and create reliable, scalable engineering workflows.

Characterize and validate PCIe interfaces on next-generation Arm SoCs across process, voltage, temperature, and frequency conditions. Develop system-level stress workloads and characterization tests in Linux and bare-metal environments, analyze silicon performance data, debug PCIe and system issues, and collaborate with validation teams to improve silicon performance and resolve defects.

Develop cycle-accurate performance models for coherent and non-coherent Arm interconnects. Collaborate with micro-architects, RTL, validation teams, and customers to assess architectural trade-offs, develop features, build performance test suites, identify bottlenecks, and deliver data-driven system performance insights. The role requires strong C++, SystemC TLM, and Python skills, plus expertise in SoC performance modeling and computer architecture.

Designs, verifies, and optimizes 2.5D and 3D system-in-package layouts for next-generation SoCs. Responsibilities include package routing, bump-map and ball-pattern optimization, stack-up and power-distribution design, feasibility studies, DFM/DFA implementation, vendor coordination, methodology development, and mentoring team members using Cadence APD and SiP tools.

Develop and analyze memory controller IP and system performance models for Arm-based SoCs. Optimize power, performance, and microarchitecture using workload analysis, simulation, and emulation. Create performance methodologies, identify system bottlenecks, guide internal teams and partners, correlate models with RTL, and mentor engineers. Requires strong computer architecture expertise, C++ development, scripting, and experience with memory or interconnect performance modeling.

Build and operate secure, scalable AI compute platform services, including backend APIs, asynchronous workflows, Kubernetes controllers, and multi-tenant workload capabilities. The role focuses on distributed training and inference, platform reliability, observability, developer tooling, and infrastructure simplification. Responsibilities include collaborating across engineering teams, improving scalability and developer productivity, and providing technical leadership for production AI platform capabilities.