Autonomy Hardware Systems Architect

Rivian•Palo Alto, CA

9d•Remote

About The Position

We are seeking a highly skilled and experienced candidate to help lead the system architecture for advanced autonomy platforms supporting commercial and personal L4 capabilities. In this position, you will lead efforts within the Autonomy Hardware team to develop a full understanding of product features and attributes, collaborate cross-functionally to translate and decompose them into technical requirements, and ultimately define their respective sub-system and constituent module architectures. In later stages of development, you will leverage these insights to help define system performance criteria and methodology for validation of these systems against their requirements. This is a wide-ranging and impactful role that begins at early stage product development and ends at manufacturing launch. You will work across the autonomy hardware and software teams to develop the autonomy compute architecture, network connectivity, and sensor/actuator systems required to support autonomous driving. This is a hands-on role that will be involved in problems large and small. Attention to detail, open communication, and strong engineering fundamentals are paramount for success.

Requirements

Advanced degree in Computer Science, Electrical Engineering or a related field, and a track record of 10+ years of hands-on experience in relevant industries, including automotive, aerospace, or relevant consumer applications.
Strong familiarity with the landscape of automotive high-compute technologies for autonomy, including DNN pipelines, camera & ISP pipelines, Radar, LiDAR connectivity and signal processing, DSP sub-systems, high-speed interfaces, and related subsystems.
Experience designing and developing embedded systems to optimize for network performance, compute and network resource utilization, power moding states and efficiency, end-to-end latencies, functional safety, and other system performance characteristics.
Hands-on experience with a variety of embedded hardware typical in automotive applications, including high-compute SoCs, MCUs, camera or other sensors, de-/serializers, transceivers, networking components, and/or related connectivity and peripheral interfaces
Strong understanding of embedded computing platforms, and the methods for quantifying performance of their processors, including CPU, GPU, NPU, DSP, ISP, etc, as well as memory systems, networking and peripheral interfaces.
Conversant with on- and off-board high-speed automotive interfaces and networks, such as PCIe, GMSL, FPD-Link, Ethernet, A2B, USB, CAN-FD, and how to characterize their utilization and performance.
Solid grasp of the power related aspects of distributed embedded architectures, including efficient utilization of low-power states, wake propagation and sequencing.
Some familiarity with automotive audio technologies including RNC, SDR, DSPs, i2s and A2B interfaces, amplifiers, mics, accelerometers and related peripherals.
Conversant with wireless technologies like GNSS, BLE, LTE, 5G, Wi-Fi, and/or UWB.

Responsibilities

Work cross-functionally with vehicle architecture, hardware design and software application teams to factor functional and performance requirements into their sub-systems, identify the key metrics and trade-offs, and optimize them using data and analysis, to distill clear system and module architecture requirements.
Model system-level trade-offs concerning distributed compute, functional safety, network and other resources, considering dimensions like power efficiency, end-to-end latencies, compute/memory utilization, and scalability, to help produce optimal systems architectures.
Guide the development of autonomy compute hardware from Proto to Production phases.
Collaborate with system performance engineers, hardware design and software teams to create comprehensive validation plans that surface key system-level performance metrics, locate bottlenecks or chokepoints, and identify over-/under-design scenarios relative to system requirements.