Full-Time

Lead Systems Signal Integrity/Power Integrity Engineer

Cerebras

Cerebras

1,001-5,000 employees

AI accelerator hardware replacing GPUs

Compensation Overview

$220k - $250k/yr

+ Bonus + Equity

Sunnyvale, CA, USA

In Person

Master's

Category
Hardware Engineering (1)
Required Skills
Printed Circuit Board (PCB) Design
Graphics Processing Unit (GPU)
High Performance Computing (HPC)

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Requirements
  • A Master's degree in Electrical Engineering.
  • At least 15 years of demonstrated expertise in system-level signal integrity and power integrity engineering for high-speed hardware systems.
  • Deep expertise in high-speed serial and parallel interface analysis and debugging.
  • Strong hands-on experience with printed circuit board, rigid-flex, and flex circuit stack-up design and analysis.
  • Advanced signal integrity and power integrity analysis of flex connectors, high-density interconnects, and advanced packaging technologies.
  • Proficiency with two-dimensional and three-dimensional electromagnetic simulation tools.
  • Experience with power delivery network analysis, simulation, and laboratory correlation at the system level.
  • Strong grounding in transmission line theory, microwave engineering, and high-speed design fundamentals.
  • Proven ability to correlate simulation results with hardware behavior and drive concrete design fixes.
  • Experience working on server hardware, artificial intelligence accelerators, hardware accelerators, datacenters, artificial intelligence hardware, enterprise products, graphics processing units, central processing units, tensor processing units, or server platforms.
Responsibilities
  • Solve complex signal integrity and power integrity problems for high-speed artificial intelligence compute platforms, including chip-to-chip and chip-to-board interfaces.
  • Perform advanced pre-layout and post-layout signal integrity and power integrity analysis across printed circuit boards, flex circuits, rigid-flex assemblies, connectors, and advanced packages.
  • Lead root-cause analysis of signal integrity and power integrity issues such as margin shortfalls, impedance discontinuities, coupling, resonances, and simulation-to-hardware mismatches.
  • Analyze and resolve signal integrity and power integrity challenges associated with flex circuits, high-speed flex connectors, interposers, and advanced packaging technologies.
  • Analyze and troubleshoot power delivery networks using direct-current and alternating-current simulations and hardware correlation to resolve performance and stability issues.
  • Define and refine printed circuit board, rigid-flex, and flex circuit stack-ups, material selections, and impedance structures to meet performance targets.
  • Review schematics, printed circuit board layouts, and flex designs to identify signal integrity and power integrity risks and recommend targeted design changes.
  • Work closely with silicon and package design teams to resolve signal integrity and power integrity issues related to bump and ball assignments, package-to-printed-circuit-board transitions, and interface interactions.
  • Act as a technical escalation point for complex signal integrity and power integrity issues across multiple programs.
Desired Qualifications
  • Experience with large-scale artificial intelligence or high-performance computing systems.

Cerebras Systems creates AI acceleration hardware and software. Its CS-2 system is designed to replace traditional GPU clusters for AI workloads, speeding up training and inference while simplifying the setup by eliminating the need for parallel programming, distributed training, and cluster management. The product works as a single, large processor-based accelerator with accompanying software and cloud services to run AI models efficiently, reducing latency and time to results. Compared with competitors, Cerebras differentiates itself with the largest processor in the industry and an integrated hardware-software stack that aims to streamline AI workflows rather than relying on multi-GPU clusters. The company’s goal is to help research labs, healthcare, finance, and other industries achieve faster, more cost-effective AI development and deployment by offering a turnkey high-performance AI compute solution.

Company Size

1,001-5,000

Company Stage

IPO

Headquarters

Sunnyvale, California

Founded

2016

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Simplify Jobs

Simplify's Take

What believers are saying

  • Q2 2026 core cloud revenue jumped 287% to $127.7 million, proving inference demand.
  • Management raised 2026 core revenue guidance to $880–890 million after beating core revenue.
  • Compute Nordic and other contracts give Cerebras over 600 megawatts contracted through 2027.

What critics are saying

  • OpenAI concentration dominates: one multiyear customer anchors the $25.4 billion backlog.
  • Q3 2026 core margin guides negative 23% to negative 25%, pressuring profitability.
  • Nvidia Blackwell and AMD Helios directly attack inference economics; Cerebras loses if customers standardize elsewhere.

What makes Cerebras unique

  • Cerebras' CS-4 pairs wafer-scale silicon with ultra-low-latency inference, launched August 18, 2026.
  • OpenAI's GPT-5.6 Sol uses Cerebras for 14x faster Ultrafast mode on August 13, 2026.
  • Cerebras signed a 165 MW Finland data-centre build with seven-year contracted capacity on September 1, 2026.

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Benefits

Professional Development Budget

Flexible Work Hours

Remote Work Options

401(k) Company Match

401(k) Retirement Plan

Mental Health Support

Wellness Program

Paid Sick Leave

Paid Holidays

Paid Vacation

Parental Leave

Family Planning Benefits

Fertility Treatment Support

Adoption Assistance

Childcare Support

Elder Care Support

Pet Insurance

Bereavement Leave

Employee Discounts

Company Social Events

Growth & Insights and Company News

Headcount

6 month growth

-2%

1 year growth

-4%

2 year growth

0%
Associated Press
Sep 1st, 2026
Cerebras and Compute Nordic launch 165 MW AI data centre in Finland with $1.9B investment

Cerebras Systems has announced a new AI data centre in Mikkeli, Finland, developed with Compute Nordic Finland. The facility will scale in phases to 165 MW of contracted IT capacity, with construction on the initial 50 MW phase already under way. The agreement includes seven-year contract terms for each service order. Independent analysis estimates the project represents an investment of €1.0–1.7 billion at full scale, supporting 80–250 direct permanent jobs and €0.8–2.5 million per year in property tax revenue. The facility is designed for efficiency, using closed-loop cooling systems and supporting waste-heat recovery. Capacity will scale from 50 MW to 80 MW to the full 165 MW as demand grows.

Yahoo Finance
Aug 25th, 2026
Cerebras shares down 40% from May peak as UBS sets $330 target with 78% upside

Cerebras Systems trades at $185.43, while the average Wall Street price target sits at $291.64, implying 57% upside. Ten of 11 analysts rate it Buy despite shares falling 40% from their May high of $311.07. The AI chipmaker's second-quarter revenue of $180.11 million missed the $193.55 million estimate. Management guided third-quarter core operating margin to negative 23% to negative 25%, down from negative 16% in the second quarter. The selloff was company-specific. Nvidia fell just 7% and AMD dropped 10% over the same period. UBS analyst Timothy Arcuri maintains a $330 street-high target, citing the pending CS-4 wafer-scale platform launch and gross margins expected to scale above 40% as yields mature.

Yahoo Finance
Aug 22nd, 2026
Cerebras core revenue up 103% to $210M as cloud quadruples but GAAP hardware sales drop 23%

Cerebras Systems reported second-quarter core revenue of $209.9 million, up 103% year-on-year and exceeding guidance of approximately $194 million. However, GAAP revenue of $180.1 million fell short of the $194.23 million consensus. The quarter revealed a sharp revenue mix shift. Cloud and other services revenue roughly quadrupled to $126 million, whilst GAAP hardware revenue declined 23% to $54.1 million. Core hardware revenue rose 17% year-on-year to $82.1 million but dropped 26% sequentially from $111.6 million. Shares fell 11.9% to $231.01 following the report. The company raised its 2026 core revenue forecast to $880–890 million from $855–865 million and reported $25.4 billion in remaining performance obligations, supported by a multiyear OpenAI agreement.

Yahoo Finance
Aug 21st, 2026
Cerebras unveils CS-4 AI system with 750 PFLOPS, 30x faster inference than GPUs

Cerebras unveiled its fourth-generation CS-4 AI system, claiming inference speeds exceeding 4,400 tokens per second per user on GPT-OSS-120B — up to 30 times faster than GPU-based solutions. The CS-4 delivers 750 PFLOPS of AI compute and 7.2 Tbps of I/O, with 10 times more throughput per watt than the previous CS-3. The company reported second-quarter 2026 core cloud and services revenues of $127.7 million, up 287% year over year. Total core revenues rose 103% to $209.9 million. Cerebras disclosed $25.4 billion in remaining performance obligations and over 600 megawatts of data-centre capacity under contract for delivery by end of 2027. The company faces competition from NVIDIA, which reported $75.2 billion in first-quarter fiscal 2027 data-centre revenues, and AMD's Helios platform.

Tech in Asia
Aug 19th, 2026
Cerebras unveils CS-4 rack with three WSE-3 Turbo chips for AI inference

Cerebras Systems unveiled its CS-4 server rack for AI inference on 18 August in San Francisco. The Sunnyvale, California-based chipmaker said the system uses three WSE-3 Turbo chips and new networking components. CS-4 is the first product based on Cerebras' Nexus architecture, a modular design for compute, power, and input/output. The system features programmable input/output and direct wafer links to connect wafers within and across racks with lower latency. The chips are manufactured using TSMC's 5-nanometre process. The launch follows Cerebras reporting an adjusted loss of $6.9 million on sales of $180.1 million last week. The system will be available in the third quarter. Cerebras competes with Nvidia in inference hardware for workloads such as chatbot response generation.