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Efficient Computer

Energy-efficient processors for edge IoT computing

Lead RTL Design Engineer

Silicon & ASIC DesignConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 8 years of RTL design experience with tape-out ownership of dataflow-based design, on-chip networks, memory subsystems, or peripheral integration on a processor or accelerator system-on-chip.
  • Deep proficiency in SystemVerilog for RTL, including synthesis-clean, lint-clean, timing-aware design of complex state machines, arbiters, token flow controllers, and datapath logic from scratch.
  • Solid understanding of parallel execution models, including dataflow, SIMD, or systolic array architectures, and familiarity with hardware challenges of token-based firing-rule evaluation and producer-consumer synchronization.
  • Hands-on experience with on-chip memory design, including SRAM wrappers, scratchpad or TCM, banking, and memory-mapped register interfaces.
  • Experience with low-power RTL techniques, including UPF-driven flows, clock gating, power domains, retention registers, and always-on wakeup logic.
  • Familiarity with at least one standard on-chip bus protocol (AXI, AHB, APB, TileLink, or NoC equivalent) at the RTL implementation level.
  • Experience taking RTL through synthesis and timing closure, including ability to read and act on SDC constraints, STA reports, and synthesis QoR summaries.
  • Strong written communication skills and ability to independently produce microarchitecture specifications and design review material.
  • Experience with memory compiler toolchains.

Responsibilities

  • Own the design and definition of processor and compute-unit microarchitecture, including dataflow pipelines, execution units, and interfaces; set performance, power, and area targets and guide the team toward achieving them.
  • Define and drive the design of on-chip networks and data movement across the fabric, balancing performance, scalability, and implementation constraints in collaboration with physical design.
  • Define the interface to the memory subsystem, including data movement, ordering, and synchronization behavior, ensuring a clean and scalable model for software and future system expansion.
  • Lead the architecture of configuration, scheduling, and execution of workloads on the fabric, including multi-kernel support and interaction with host systems.
  • Drive power architecture across the design, including clocking, reset, power domains, and low-power strategies to meet energy and efficiency goals.
  • Collaborate with compiler and software teams to define the hardware execution model and ensure efficient mapping of workloads onto the architecture.
  • Author and own microarchitecture specification documents for assigned blocks; drive design reviews with architecture, compiler, design verification, and physical design stakeholders.
  • Mentor senior and junior RTL engineers; review RTL, flag microarchitecture risks, and enforce coding style and lint-clean standards across the team.
  • Participate in PPA analysis loops by regularly synthesizing blocks, reviewing area, timing, and power reports, and making data-driven tradeoffs against performance and feature requirements.
  • Collaborate with design verification leads to define and review verification plans; provide directed test scenarios for graph execution corner cases, back-pressure conditions, and power state transitions.
  • Support silicon bring-up by contributing scan and ATPG guidelines, reviewing design-for-test insertion, and providing RTL-level debug assistance during lab validation.

Desired Qualifications

  • Prior RTL ownership of a dataflow engine, neural processing unit, or streaming DSP architecture with explicit producer-consumer token management.
  • Experience collaborating with compiler or graph-optimization teams to co-design hardware execution models and graph intermediate-representation formats.
  • Familiarity with non-volatile memory controller RTL (MRAM, RRAM), including ECC, program/erase sequencing, and model-weight storage use cases.
  • Experience with IoT-class power budgets (sub-10 mW active, sub-100 µW standby) and the RTL design choices they necessitate.
  • Familiarity with functional safety standards (ISO 26262, IEC 61508) as applied to execution-fabric error detection and power-domain isolation.
  • Exposure to AI framework graph formats (ONNX, TFLite) and understanding of how graph compilation maps to hardware execution primitives.
  • Tape-out credits on an edge-AI, IoT, or wearable system-on-chip at 12nm or below.
  • Experience with formal verification of flow-control logic, deadlock freedom, or bus protocol compliance.

About the Company

Efficient Computer

Energy-efficient processors for edge IoT computing

Efficient Computer makes energy-efficient programmable processors for IoT edge devices and sells a compatible software toolchain that fits existing embedded languages and AI/ML workflows. These processors run local computations at the edge, reducing the need to send data over wireless links, which saves power and enables real-time processing and data compression. Its strength comes from combining hardware with a developer-friendly ecosystem rather than relying on general-purpose chips, helping deployments last longer in places without wired power. Its goal is to enable widespread, cost-effective edge deployments by dramatically lowering energy use and total cost of ownership for IoT networks.

Company size
51-200
Company stage
Series B
Total funding
$173M
Headquarters
Pittsburgh, PA
Founded
2022

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