About Graphcore
At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary

We are looking for an experienced Silicon Test Engineer to join our Product Test and Diagnosis Department (PTD).

This is a pivotal role and will involve building a team of engineers to develop System Level Test (SLT) capability within the company. Working closely with a cross-functional team you will implement SLT tests for a family of next generation AI Processors.

The ideal candidate should have a focus on quality and demonstrate a good understanding of the importance of production test on the success of a product.

They will have a proven Functional Test or ATE Test Engineering background, and will have a pragmatic, hands-on and flexible approach to a fast-changing environment.

The Team

The Product Test and Diagnostics team’s role is to detect and manage hardware defects that arise from the manufacture and use of our products. This covers chips, boards and finished systems and takes place both in the manufacturing sites and in the field.

Responsibilities and Duties

Managing a team of engineers to implement SLT test solutions for a multi-die AI Processor product

Working with the Silicon, Test and DFT teams to define manufacturing test solutions

Working with key industry leaders to develop an SLT system capable of meeting the products needs

Understanding of top, and board level DFT strategies within a 3D, multi-die product

Understanding of implementation details for an Incoming Quality Inspection (IQC) stage, and the inter-department complexities

Defining test fixtures for SLT Test Solutions: Structural and functional test equipment, interface PCBs, sockets, cooling systems, etc

Writing Production, Engineering and Characterisation Test Programs on Advanced SLT platforms

Working with other departments to balance test coverage and fault detection across all test stages in the flow; ATE, board, blade, and in-field test

Correlation to bench measurements

Transferring test solutions to the offshore vendors, as part of an NPI release

Work collaboratively with other engineering teams to ensure successful silicon, and board bring-up and help identify any silicon failures to enhance yield learning and improvement

Candidate Profile

Essential:

A pragmatic approach, the ability to improvise, pitch in, and get the job done

Experience in production test of large digital devices

Very good knowledge of digital integrated circuits and advanced test techniques

Very good understanding of DFT components such as (i)JTAG (IEEE 1149.x), BIST, MBIST, etc

Understanding of functional test of complex systems

Experience in transferring to volume manufacture to OSATs and Contract Manufacturers

Ability to work within high pressure cross-department and cross-company teams

Ability to mentor junior members of the team

Strong scripting and debugging skills using programming languages like Python, TCL, Perl, Shell etc

Degree level qualifications in electronics or a related field

Good communication skills

Desirable

Proven competence on SLT testers

Experience of thermal control of high-power devices in a production environment.

Benefits
In addition to a competitive salary, Graphcore offers flexible working and a comprehensive benefits package designed to support your health, wellbeing and financial future. Our benefits include medical, dental and vision coverage, Flexible Spending Accounts (FSAs), Health Savings Accounts (HSAs), disability and life insurance, a 401(k) retirement plan, commuter benefits, wellness services and an Employee Assistance Programme (EAP). We welcome people of different backgrounds and experiences; we're committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

About the company

Graphcore.ai focuses on building and delivering Intelligence Processing Units (IPUs) and related AI services for enterprises. It provides IPU-powered cloud services, pre-trained AI models, optimized inference engines, and APIs on a subscription basis with on-demand pricing and free tiers through cloud partners. The IPUs accelerate AI workloads and enable scalable, cost-efficient AI deployment in enterprise applications. The company differentiates itself through specialized IPU hardware and optimized software stack, plus partnerships with cloud providers to reach customers, rather than relying on generic hardware. The goal is to help businesses scale AI-powered products and operations efficiently by offering flexible, scalable compute and ready-to-use AI components.

Company Size

501-1,000

Company Stage

Growth Equity (Non-Venture Capital)

Total Funding

$1.1B

Headquarters

Bristol, United Kingdom

Founded

2016

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Simplify's Take

What believers are saying

SoftBank injected $457 million on May 12, 2026, extending Graphcore's runway.
Graphcore's July 2026 Bengaluru expansion accelerates hiring across silicon and software.
Graphcore posted 175 job openings in 2026, signaling renewed operating momentum.

What critics are saying

Nigel Toon stepped down July 31, 2026, removing Graphcore's founding face.
Graphcore exited China in 2025 after layoffs, losing 20%-25% of sales.
Nvidia CUDA and Blackwell dominate AI compute; Graphcore survives only through SoftBank funding.

What makes Graphcore unique

Graphcore IPUs target sparse ML workloads with chip-level model execution.
SoftBank owns Graphcore since 2024, linking it to Arm and Stargate.
Bengaluru campus plans £1 billion and 500 semiconductor jobs over ten years.

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Benefits

Health Insurance
Dental Insurance
Life Insurance
401(k) Retirement Plan
401(k) Company Match
Flexible Work Hours
Paid Vacation
Mental Health Support
Parental Leave

Growth & Insights and Company News

Headcount

6 month growth

10%

1 year growth

2 year growth

TechSpark

Aug 7th, 2026

Tech News roundup - 31.07.26.

Tech News roundup - 31.07.26. Welcome to our weekly South West Tech News roundup, where you can get all the headlines from the past week in one place. What has our busy tech and digital community been up to this week? From award wins and innovative breakthroughs to unmissable events and capital raised, take a moment to reflect on the hive of daily activity taking place in our region. If you have a story to share, fill out the following form here. IT firm Intercity targets South West growth with Bristol Bears partnership. IT solutions provider Intercity is expanding into the South West through a new partnership with Bristol Bears. As the club's official IT solutions provider, Intercity will deliver managed IT, cloud and cybersecurity support across the men's and women's teams, while growing its presence in the region. Read the full news here Bristol sports tech firm secures £500k to expand data-driven platform. Bristol-based Levels Technologies has raised £500,000 to scale its data-driven rankings and community platform across global racket sports. Having built a strong following in squash, the company is now expanding into padel and other sports, using performance data to help players track progress, find better-matched opponents and connect with their communities. Read the full news here Isambard-AI marks first year powering UK research breakthroughs. The University of Bristol's Isambard-AI, the UK's most powerful AI supercomputer, is celebrating its first year after supporting around 1,000 research projects and more than 4,000 users. From dementia research and AI safety to climate science and animal welfare, the £225 million facility is helping researchers tackle challenges previously beyond the UK's computing capabilities. Read the full news here Bristol IT firm strengthens team with three key appointments. Bristol-based WestSpring IT has strengthened its team with three senior appointments as it continues its next phase of growth. The expansion follows the company's recent recognition in the IT Channel Oxygen Fast-Growth 50 for 2026, highlighting it as one of the UK's fastest-growing managed IT service providers. Read the full news here Graphcore co-founder steps down to focus on new AI venture. Nigel Toon, co-founder of Bristol AI chip pioneer Graphcore, has stepped down after a decade with the company. Toon will now focus on BlankPage Capital, his new venture supporting emerging deep-tech, semiconductor and AI businesses to grow and scale, while Graphcore enters its next chapter under new leadership. Read the full news here £150m extreme environment testing centre planned for the South West. The South West has been selected as the planned location for the £150 million NauteXe Extreme Environment Centre, a world-leading facility for testing technologies in challenging conditions spanning the deep ocean, offshore wind and space. Set for Exeter Science Park, the centre could generate more than £500 million in wider economic impact and strengthen the region's position in defence, maritime autonomy and advanced engineering. Find out more here

VentureBurn

May 13th, 2026

Graphcore raises $450M to expand AI chip ambitions.

Graphcore raises $450M to expand AI chip ambitions. 13 May 2026 Key Takeaways * SoftBank has invested $457 million into Graphcore, marking the largest single funding boost since the company was acquired in 2024. * The funds are specifically intended for developing hardware that supports Artificial General Intelligence (AGI), moving beyond standard machine learning. * A significant portion of the capital will fund a £1 billion AI campus in Bengaluru, signalling a shift toward global engineering hubs. Graphcore has raised a $457 million capital investment from parent company SoftBank Group. The injection of funds has been confirmed during this week after its regulatory filings and shows SoftBank's unrelenting plan of concerted efforts to create a vertically integrated artificial intelligence system to take on industry leaders such as Nvidia. This financing occurs within 2 years of SoftBank, which bought the Bristol company in July 2024 for an undisclosed amount. Once valued at $2.8 billion as an independent startup, Graphcore is now being positioned as a key component of the broader Artificial General Intelligence (AGI) ambitions of Masayoshi Son. Fueling the Stargate era. According to filings at Companies House, Graphcore issued a single share valued at approximately $457 million in April 2026. A spokesperson for the company confirmed that these funds are part of a multi-stage financing plan from SoftBank intended to scale Graphcore's research, development and global footprint throughout the year. The capital arrives at a critical juncture. SoftBank is currently a lead participant in the $500 billion Stargate project, a massive AI infrastructure initiative in partnership with OpenAI and Oracle. Industry analysts suggest that Graphcore's IPU technology is being groomed to provide the specialised silicon needed for the massive data centres required by the next generation of large language models. "Graphcore's expertise in chip design complements our existing leadership in semiconductor IP through Arm," SoftBank CEO Masayoshi Son previously noted. The new funding suggests that the rebuilding phase for Graphcore is over, and the company is now moving into a high-growth execution phase. Global expansion: the Bengaluru campus. The new capital's main potential target is India. Graphcore announced the intention to pump in as much as £1 billion (more than $1.25 billion) in a giant new AI centre in the means of Bangalore. The site is to employ hundreds of engineers for silicon design, software and other AI infrastructure. By moving much of its engineering weight to India, Graphcore hopes to access one of the largest pools of semiconductor talent in the world and reduce costs. The move will be vital in competing against the dominant market share of Nvidia. A new leadership and direction. The funding also follows a period of internal transformation. Following the SoftBank acquisition, co-founder Nigel Toon stepped down as CEO, making way for new leadership. The new leadership is more closely aligned with SoftBank's broader ecosystem, which includes the recently acquired Ampere Computing. Graphcore struggled to gain commercial traction against Nvidia's CUDA platform as a standalone entity. However, its integration into SoftBank gives it a captive market. With SoftBank's influence over data centre builders and deep ties to AI labs, Graphcore's IPUs may find scale. This scale had eluded Graphcore for years. As demand for energy-efficient, AI-specific silicon skyrockets, this $450 million bet signals strong intent. The British Nvidia is not just surviving under its new owners; it is preparing to lead. I'm a crypto writer with 4+ years of experience passionate about turning big, technical ideas into content anyone can understand. From blockchain to stablecoins to everything in between, I enjoy helping readers stay informed in a space that never stops moving. Disclaimer VentureBurn is a media platform covering the latest in cryptocurrency, artificial intelligence, venture capital, and the startup ecosystem. Opinions expressed on VentureBurn are for informational purposes only and do not constitute investment advice. Before making any high-risk investments in digital assets or emerging technologies, readers should conduct their own due diligence. All transactions and financial decisions are made at your own risk, and any losses incurred are solely your responsibility. VentureBurn does not endorse or recommend the buying or selling of any digital assets and is not a licensed investment advisor. Please note that VentureBurn may participate in affiliate marketing programs.

CNBC

May 12th, 2026

SoftBank injects $450M into British AI chip company Graphcore

SoftBank has injected $457 million into British AI chip company Graphcore, according to a Companies House filing. The funding, issued as a single share on 10 April, represents a portion of the money Graphcore expects from SoftBank this year, according to a person familiar with the arrangement. SoftBank acquired Graphcore in 2024, with plans for the company to collaborate on developing artificial general intelligence. Once touted as a rival to Nvidia, Graphcore raised hundreds of millions of dollars but struggled to gain commercial traction before the acquisition. The investment follows SoftBank's recent AI infrastructure push, including involvement in the $500 billion Stargate project with OpenAI and Oracle. In October, Graphcore announced plans to invest up to £1 billion in a new AI campus in Bengaluru, India.

Make AI Prompt

Apr 3rd, 2026

AI News Today | New AI Chips News: Performance Boost Claims.

AI News Today | New AI Chips News: Performance Boost Claims. The AI industry is constantly pushing the boundaries of hardware capabilities, and recent announcements surrounding AI News Today | New AI Chips News: Performance Boost Claims highlight this ongoing race. Several companies are asserting significant performance improvements in their latest AI chip designs, promising faster processing, reduced energy consumption, and enhanced capabilities for AI applications. These claims, if validated, could drastically impact the speed and efficiency of everything from cloud computing to edge devices, accelerating the deployment and advancement of AI across various sectors. The industry is watching closely to see which of these performance boosts translate into real-world advantages. Contents [hide] Understanding the latest AI chip performance claims. The core of AI News Today | New AI Chips News: Performance Boost Claims often revolves around specific metrics. Companies typically highlight improvements in teraflops (trillions of floating-point operations per second), power efficiency (performance per watt), and latency (the delay in processing information). These metrics directly impact the ability of AI systems to handle complex tasks like natural language processing, image recognition, and machine learning model training. A higher teraflop count generally indicates a chip's ability to perform more calculations in a given time, leading to faster processing. Better power efficiency translates to lower operating costs and a reduced environmental footprint, making AI more sustainable. Lower latency is crucial for real-time applications, such as autonomous vehicles and robotics, where immediate responses are essential. Machine Learning & Artificial Intelligence Key players in the AI chip market. The AI chip market is dominated by a mix of established tech giants and specialized startups, all vying for a piece of this rapidly growing sector. Companies like NVIDIA, Intel, and AMD continue to innovate in traditional GPU and CPU architectures, adapting them for AI workloads. At the same time, newer players like Graphcore and Cerebras Systems are developing entirely new chip architectures designed specifically for AI, such as wafer-scale integration and massively parallel processing. Each company brings its own unique approach to the challenge of accelerating AI, leading to a diverse range of hardware solutions. Examining the impact of enhanced AI chip performance. The performance improvements promised in AI News Today | New AI Chips News: Performance Boost Claims have far-reaching implications across various industries. In cloud computing, faster and more efficient AI chips can enable cloud providers to offer more powerful AI services to their customers, supporting everything from data analytics to AI-powered applications. In edge computing, improved chip performance can bring AI capabilities closer to the data source, enabling real-time processing and reducing reliance on cloud connectivity. This is particularly important for applications like autonomous vehicles, industrial automation, and smart cities, where low latency and reliable performance are critical. AI tools and the need for faster processing. The development and deployment of AI tools, including tools that generate a list of AI Prompts, relies heavily on computational power. As AI models become more complex and data sets grow larger, the demand for faster processing continues to increase. Whether it's training a new natural language model or running inference on a large dataset, AI chips play a crucial role in determining the speed and efficiency of these tasks. A powerful Prompt Generator Tool, for example, needs to rapidly process user input and generate relevant prompts, which requires significant computational resources. Machine Learning & Artificial Intelligence Discover more Business & Productivity Software Text & Instant Messaging Machine Learning & Artificial Intelligence How new chips are reshaping AI strategy. The advancements highlighted in AI News Today | New AI Chips News: Performance Boost Claims are not just about incremental improvements; they are fundamentally reshaping AI strategy. Businesses are now able to tackle more complex AI problems, develop more sophisticated AI applications, and deploy AI solutions in new and innovative ways. The availability of faster and more efficient AI chips is also driving down the cost of AI, making it more accessible to a wider range of organizations. This democratization of AI is fostering innovation and driving adoption across various sectors. Challenges in validating AI chip performance claims. While the performance claims surrounding new AI chips are often impressive, it's important to approach them with a degree of skepticism. Validating these claims can be challenging, as performance can vary significantly depending on the specific workload, software environment, and system configuration. Companies often use benchmark tests to demonstrate the performance of their chips, but these tests may not always accurately reflect real-world performance. Furthermore, power consumption and latency are often overlooked in these marketing materials, even though they are critical factors in many applications. Independent testing and validation are essential to ensure that these claims are accurate and reliable. Machine Learning & Artificial Intelligence Discover more Machine Learning & Artificial Intelligence Text & Instant Messaging Business & Productivity Software The role of software optimization. The performance of an AI chip is not solely determined by its hardware capabilities. Software optimization plays a critical role in unlocking the full potential of the chip. Optimized compilers, libraries, and frameworks can significantly improve the performance of AI applications, allowing them to run more efficiently on the underlying hardware. Companies like NVIDIA invest heavily in software optimization, providing developers with tools and resources to maximize the performance of their GPUs. This highlights the importance of a holistic approach to AI hardware and software development. Future implications for users, developers, and businesses. The ongoing advancements in AI chip technology have significant implications for users, developers, and businesses. Users can expect to see more powerful and intelligent AI applications in the products and services they use every day, from smartphones to autonomous vehicles. Developers will have access to more powerful tools and resources for building and deploying AI models. Businesses will be able to leverage AI to improve their operations, create new products and services, and gain a competitive advantage. The OpenAI API, for example, is constantly being updated to take advantage of the latest hardware advancements, enabling developers to build more sophisticated AI applications. Navigating the evolving landscape of AI hardware. The AI hardware landscape is constantly evolving, with new architectures, technologies, and companies emerging all the time. It's crucial for businesses and developers to stay informed about these developments and to carefully evaluate the different options available to them. Factors to consider include performance, power efficiency, cost, software support, and long-term roadmap. Engaging with industry experts, attending conferences, and reading industry publications can help organizations navigate this complex landscape and make informed decisions about their AI hardware investments. The continuous stream of AI News Today | New AI Chips News: Performance Boost Claims underscores the relentless innovation in AI hardware, and this matters significantly because it directly impacts the capabilities and accessibility of AI across all sectors. As chip technology advances, MakeAIPrompt can anticipate more sophisticated AI applications, greater efficiency, and wider adoption. Readers should closely monitor developments in chip architecture, power efficiency, and software optimization to fully grasp the potential and the limitations of these new technologies as they shape the future of artificial intelligence. 07/02/2026 20/12/2025 10/03/2026 27/12/2025 13/02/2026 19/12/2025 03/04/2026 01/01/2026 26/12/2025 27/12/2025 21/12/2025 19/02/2026 18/12/2025 03/02/2026

DIGITIMES

Oct 15th, 2025

Graphcore to invest GBP1 billion in Bengaluru AI engineering campus, creating 500 semiconductor jobs

Graphcore to invest GBP1 billion in Bengaluru AI engineering campus, creating 500 semiconductor jobs. Graphcore, a wholly owned subsidiary of SoftBank, announced plans to establish a new AI Engineering Campus in Bengaluru, India, with an investment of up to GBP1 billion (approx. US$1.26 billion) over the next decade. The project is expected to create... * Full access to articles dating back to 2000. * Real-time access to the news as it breaks. * Access to premium content. * Full access to Tomorrow's Headlines. * Asia Supply Chain 250 dataset access.

Graphcore

Principal System Level Test Engineer

About the job