Semiconductor Process Analyst at SemiAnalysis

About SemiAnalysis

SemiAnalysis is an independent research and analysis firm specializing in the Semiconductor and AI industries. Our in-depth coverage spans the entire supply chain, from semiconductor fabrication processes to cutting-edge AI Models, software, and infrastructure. We are recognized as the leading authority on the semiconductor supply chain, with the highest concentration of industry experts within one team, and a deep-rooted passion for delving into the intricacies.

We’re a global team of over 20 analysts, each with extensive networks across the semiconductor supply chain and AI ecosystem, publishing industry‑shaping articles while participating in 40+ conferences annually.

Our newsletter reaches more than 200 000 subscribers worldwide, including senior management and C‑suite leaders at the leading semiconductor and AI companies.

We also offer three core products:

• Industry Models – we develop and publish industry models on accelerator shipments, datacenter demand and supply, GPU total cost of ownership, and more. We work with hyperscalers, neoclouds, many of the world’s largest hedge funds, and government agencies.
• Core Research – our public equity markets product, geared towards financial investors, distills our deep technical research and knowledge into key insights on technology and product trends.
• Consulting and Technical Due Diligence – We conduct custom research and project work to guide key strategic and investment decisions for the largest private‑equity funds, leading venture‑capital firms, companies across the AI ecosystem, and government agencies.

Find out more here: https://semianalysis.com

Position Overview

We are seeking an experienced, clever and motivated Semiconductor Process Analyst with a background in failure analysis, reliability, or process engineering to join our team to join our team in the United States. This role is responsible for the hands-on analysis of AI and datacenter manufacturing innovations, from the system level down to the transistor. This role requires a mix of technical expertise, sensibility, and autonomy. You’ll need to work independently, collaborate across our globally distributed team, and deliver insights on cutting edge manufacturing process and design choices, optimizations, and trade-offs.

Key Responsibilities

• Conduct detailed manufacturing and process analysis of AI and datacenter hardware (e.g., GPUs, ASICs, CPUs, and associated systems).
• Analyze and document semiconductor manufacturing processes, including FEOL, BEOL, and advanced packaging techniques, based on physical inspection and acquired data.
• Identify competitive advantages, disadvantages, and generational changes based on these findings.
• Monitor and report on trends in semiconductor technology, process development, and device research.
• Perform as a recognized authority in the current state of the art in AI and datacenter process architectures.
• Work with design experts and market analysts to develop actionable market insights and reports.

Qualifications

• 3+ years of experience in packaging, BEOL, or FEOL engineering or a reasonably equivalent role, e.g. as a Reliability Engineer, Debug Engineer or Failure Analysis Engineer.
• Direct experience in the broad areas of debug, physical failure analysis, or fault isolation.
• Functional knowledge of process integration or product architecture on advanced nodes.
• Understanding of Design Technology Co-Optimization (DTCO) principles and their application.

Nice to Have

• Experience in process or design R&D related to advanced packaging (e.g., 2.5D/3D), high-speed interconnects, and general advanced compute.
• Broad understanding of advanced manufacturing processes across CMOS logic, memory (HBM, GDDR), and emerging technologies.
• Hands-on experience with sample prep and analytical tools, SEM, (P)FIB, STEM, EMMI/IREM, *BIRCH, nanoprobing, etc.
• Proven ability to interpret analytical data, such as micrographs and materials, to infer process and design characteristics.
• Familiarity with Python for data analysis and complex engineering tasks.
• Strong professional network of experts with whom you comfortably and regularly communicate.
• Strong organizational skills and an understanding of statistics and process controls.