Engineering experience behind Interface Silicon

Meet
Ron Amir.

Interface Silicon is an independent engineering business led by Ron Amir, specializing in chip design, FPGA development, and AI acceleration. With six years of operation and dozens of clients served, the business brings hands-on engineering expertise to projects for customers in the United States, Europe, and worldwide.

Clients work directly with Ron across microarchitecture, RTL development, functional validation, and system integration.

Professional background

Experience across the system.

The roles below describe Ron’s professional background, separately from the clients of Interface Silicon.

Intel

Core IP Design & Integration · 5 years

At Intel, Ron worked across multiple core-related IP blocks, combining block-level development with the demands of a tightly integrated processor system. His work connected microarchitectural decisions, RTL implementation, and validation with broader integration and performance requirements.

Microarchitecture & RTL. Defined block-level microarchitecture and developed RTL for datapaths, control logic, pipelines, and interfaces.
Functional Validation. Investigated simulation failures, corner cases, and assertion results, collaborating with verification teams to identify root causes and validate fixes.
Integration & Performance. Addressed cross-block interactions, clock and reset behavior, data flow, and processing bottlenecks during IP integration.

Apple

iPhone Camera & Image Processing · 2 years

At Apple, Ron worked on iPhone camera hardware, with responsibility for a central image-processing unit and a particular focus on autofocus. His role connected dedicated processing hardware with the functional and latency requirements of the wider camera pipeline.

Image Processing & Autofocus. Owned hardware functionality within a central image-processing unit, with an emphasis on autofocus operation and coordination.
Microarchitecture & RTL. Developed image-processing and autofocus logic, addressing control flow, data handling, interfaces, and latency requirements.
Validation & Integration. Debugged and validated hardware behavior within the camera pipeline, coordinating interactions with surrounding hardware and system teams.

AI Data-Center Silicon

DPU Design & Integration · 3 years

Ron spent three years at an AI data-center semiconductor company, working on DPU functionality supporting data movement and processing-resource utilization. His work focused on the relationship between delivering data efficiently and keeping computational resources productively occupied.

DPU Microarchitecture & RTL. Developed hardware functionality and data paths supporting data movement within AI data-center chips.
Throughput & Resource Utilization. Addressed flow control, buffering, and data-path bottlenecks to support efficient use of processing resources.
Validation & System Integration. Validated and debugged cross-block behavior, resolving integration issues between data-transfer functionality and computational components.

FPGA-Based AI Acceleration

2 years of development

Ron spent two years developing an FPGA-based AI accelerator, combining programmable-logic engineering with the practical requirements of AI computation. This experience complements his ASIC background with hands-on accelerator development on FPGA platforms.

Accelerator Development. Developed an FPGA-based AI accelerator, connecting AI processing requirements with a hardware implementation.
System Perspective. Brought together experience in computation, data movement, and integration to address accelerator-level engineering challenges.
Corporate Training. Delivered professional courses in the field to several companies, translating complex hardware concepts into structured technical instruction.

Direct engineering collaboration.

Interface Silicon provides a direct working relationship with the engineer responsible for the project. Engagements can focus on a specific hardware block, a validation or integration challenge, or a broader development effort spanning chip design and RTL, FPGA development, and AI accelerator engineering.

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