Graduate Software Engineer, AI/ ML Test Systems 2027

Posted Yesterday
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Bristol, England, GBR
Hybrid
Entry level
Artificial Intelligence • Semiconductor
Joining Graphcore gives you a seat at the top-table, shaping the future of Artificial Intelligence.
The Role
Develops software tests for machine learning workloads on Graphcore accelerator hardware. Responsibilities include creating representative workloads, analyzing numerical accuracy and performance, designing tests, improving test infrastructure, building CI/CD pipelines, debugging issues, and collaborating with development teams to improve software quality. The two-year graduate program provides practical experience across machine learning, automation, performance analysis, and simulated and physical hardware platforms.
Summary Generated by Built In

Location: Bristol, UK
Start date: September 2027
Application deadline: Midnight, 29th November 2026 
We encourage you to apply early, as we may close applications before the advertised deadline.

The Graduate Programme at Graphcore

Join Graphcore in a permanent role and start your career with two years of hands-on learning. From day one, you’ll be trusted to take ownership, share your ideas and help shape what we’re creating. You’ll tackle challenging problems alongside a team who support your development and are as excited about your success as you are. 

What you’ll work on 

Put your software skills to work testing how AI and machine learning workloads run on Graphcore accelerator hardware. 

As a Graduate Software Engineer in AI/ML Test Systems, you’ll create representative machine learning workloads and analyse their numerical accuracy and performance. You’ll design tests and help improve testing strategies and infrastructure across simulated and physical hardware. 

You’ll also build continuous integration and continuous delivery (CI/CD) pipelines, investigate difficult problems and turn your findings into measurable improvements. Your work will connect machine learning frameworks and models with the hardware beneath them, helping improve software quality and customer experience. 

Your team and support 

The Software QA team combines software engineering, automation and data analysis to improve product quality and customer experience. We work extensively with industry-standard machine learning frameworks and models, including contributions to upstream open-source projects.  

Our team works in small squads, each with ownership of a particular area of software quality. As a graduate, you’ll have the opportunity to explore the breadth of our work, gain practical experience across different areas and discover what interests you before settling into a squad.  

You’ll work alongside engineers who investigate problems, share findings and collaborate closely with development teams to improve quality, security and maintainability. Test results, performance data and the needs of the wider software organisation guide our decisions.  

You’ll have a buddy to help you find your feet and a manager who will support your development, explore your career goals with you and help make time for learning. You’ll be encouraged to ask questions, challenge existing approaches and take initiative, with experienced colleagues to turn to for guidance as you build confidence and take ownership of your work. 

How you’ll learn and grow 

During the two-year programme, you’ll build practical experience across machine learning, testing, automation and performance analysis. 

Creating workloads and analysing results will help you understand how software behaves on accelerator hardware. Debugging issues will develop your problem-solving skills and help you connect numerical accuracy and performance to the systems running a model. 

Work on test infrastructure and CI/CD will show you how automated checks support software development across simulated and physical platforms. Sharing findings with development teams will help you explain technical problems clearly and turn evidence into improvements. 

What we're looking for 
  • Bachelor’s/Master’s degree in Computer Science, Maths, Machine Learning, Data Science or a related field 
  • Strong Python skills and proficiency in C++ 
  • Experience working with Linux operating systems and the ability to learn new technologies quickly 

Exposure to machine learning frameworks such as PyTorch, JAX, Triton or TensorFlow, test automation, CI/CD, data analytics, hardware architectures or compilers would be useful. 

Experience with distributed workload management systems or machine learning operations (MLOps) pipelines would also be useful. These are additional strengths, rather than essential requirements. 

Benefits
  • Flexible working: Balance your work and personal life with greater flexibility
  • Retirement planning support: Up to 5% matched pension
  • Phantom equity: Share in Graphcore’s success
  • Workplace experience: Enjoy thoughtfully designed office spaces for collaboration, with free food and an on-site barista to support your day
  • Peace of mind protection: Income protection and life assurance to provide financial security for you and your loved ones
  • Electric Vehicle Scheme: Choose an electric vehicle and lease it through salary sacrifice
  • Flexible benefits: Tailor your benefits package with a choice of additional options, including private medical insurance and dental cover
  • Optional benefits: Dental cover, health cash plan, private medical insurance, cycle to work scheme, give as you earn

We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work.
We’re an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know - we’re happy to support you.

Sponsorship

Applicants must already have the right to work in the UK for the full duration of the programme, without requiring visa sponsorship. We are unable to sponsor work visas for our Early Careers opportunities.

Introduction to Graphcore

At Graphcore, we’re building next generation AI compute: from semiconductors and software to systems at datacenter scale. We are proud to be owned by SoftBank Group and work with other companies in the SoftBank family to deliver AI compute to customers working at the AI frontier. Starting your career here means working alongside people with different backgrounds and expertise, from AI researchers to chip designers and software engineers. You’ll learn from each other, bring fresh ideas and help solve challenging problems together.

How to apply and what to expect 

To apply, answer the application questions below and upload your CV and cover letter. We’ll let you know the outcome of your application by early December at the latest. If successful, you’ll be invited to complete a technical assessment. Candidates who reach the final stage will then be invited to attend in-person assessments in early spring.

Ready to put your learning into practice? Start your career in a permanent Software Engineer role in AI/ML Test Systems, with two years of hands-on learning through the Graphcore Graduate Programme. Apply now and help shape what comes next. 

Skills Required

  • Bachelor's or Master's degree in Computer Science, Mathematics, Machine Learning, Data Science, or a related field
  • Strong Python skills
  • Proficiency in C++
  • Experience working with Linux operating systems
  • Ability to learn new technologies quickly
  • Exposure to machine learning frameworks such as PyTorch, JAX, Triton, or TensorFlow
  • Experience with test automation
  • Experience with CI/CD
  • Experience with data analytics
  • Knowledge of hardware architectures or compilers
  • Experience with distributed workload management systems
  • Experience with MLOps pipelines
  • Existing right to work in the UK for the full duration of the program without visa sponsorship

What the Team is Saying

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Graphcore Compensation & Benefits Highlights

  • Healthcare Strength — Company materials list private medical insurance, dental coverage, health cash plans, mental‑health support, and day‑one U.S. medical options via Cigna/Kaiser. Feedback suggests these offerings are a meaningful strength, particularly in the UK.
  • Leave & Time Off Breadth — Benefits highlight flexible working hours, unlimited annual leave, generous parental leave, and paid U.S. holidays. Feedback suggests work‑life balance is often described positively alongside these policies.
  • Retirement Support — UK information cites pension matching up to 5%, while U.S. listings describe a 401(k) with a 100% company match up to 6%. Feedback suggests these structured contributions are viewed as competitive elements of the package.

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The Company
HQ: Bristol, Bristol
903 Employees
Year Founded: 2016

What We Do

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.

Why Work With Us

Our team is at the forefront of the machine intelligence revolution, enabling innovators from all industries to build AI-native products to expand human potential. What we do at Graphcore really makes a difference.

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Graphcore Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

At Graphcore, we value wellbeing and flexibility to support a healthy work/life balance. Our hybrid approach encourages office-based colleagues to work onsite three days a week, with trusted flexibility built on trust and transparency for everyone.

Typical time on-site: 3 days a week
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