Staff Engineer (ML Engineer) in London

Staff Engineer (ML Engineer) in London

London Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Benchmark and validate ML models, ensuring performance and reliability across various environments.
  • Company: Join Graphcore, a leader in AI compute backed by SoftBank, shaping the future of technology.
  • Benefits: Enjoy flexible working, generous leave, private health insurance, and a vibrant office culture.
  • Other info: Inclusive workplace committed to diversity, with excellent career growth opportunities.
  • Why this job: Make a real impact in AI while collaborating with top minds in a dynamic environment.
  • Qualifications: Experience in ML engineering, strong Python skills, and familiarity with major ML frameworks required.

The predicted salary is between 63000 - 77000 £ per year.

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 Soft Bank Group, backed by significant long‑term investment, we are delivering key technology into the fast‑growing Soft Bank 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

Applicants for this role should have strong experience working with machine learning systems and frameworks, along with a solid understanding of core AI concepts and model behaviour.

The role centres on testing, validating, and benchmarking a complex ML software stack, with a particular focus on performance, reliability, and correctness across modern AI workloads.

The ideal candidate is an experienced ML engineer who understands how contemporary models are trained and executed, and who has hands‑on experience debugging functional and performance issues in ML systems.

This person will be comfortable working with industry‑standard frameworks and state‑of‑the‑art models, bringing them up on internal infrastructure, and collaborating closely with software and hardware teams in a technically demanding environment spanning ML frameworks, infrastructure, and AI accelerator hardware.

The Team

The MLQA team is composed of highly skilled software engineers with a strong focus on automation, software quality, and data‑driven validation.

The team works closely with industry‑standard machine learning frameworks and models, contributing to upstream open‑source projects and collaborating across the wider software organization.

Operating in a fast‑paced environment, the team plays a critical role in ensuring reliability, performance, and maintainability across the ML software stack, helping to deliver robust and high‑quality products to customers.

Responsibilities and Duties

  • Benchmark ML models and frameworks, analysing results to identify regressions, performance bottlenecks, and correctness issues.
  • Work hands‑on with industry‑standard ML frameworks to validate functionality and performance across different execution environments.
  • Build and maintain automated testing and benchmarking pipelines targeting simulators, emulators, and physical hardware.
  • Collaborate closely with software teams to ensure adequate test coverage for new and existing features.
  • Develop tooling and scripts (primarily in Python) to support testing, benchmarking, and functional reporting.
  • Take ownership over aspects of our testing and infrastructure, owning the roadmap and driving innovation independently.
  • Candidate Profile
  • Experience working in Machine Learning or ML‑adjacent engineering roles.
  • Strong foundation in core AI and ML concepts (e. g. neural networks, training vs inference, numerical precision, performance trade‑offs).
  • Hands‑on experience with one or more major ML frameworks such as Py Torch, Tensor Flow, JAX, or similar.
  • Strong proficiency in Python for ML workflows, experimentation, and automation.
  • Experience designing, running, and analysing ML benchmarks or experiments.
  • Experience working in Linux environments.
  • Strong analytical and debugging skills, with the ability to reason about model behaviour and system performance.
  • Bachelor/Master’s/Ph D or equivalent experience in Computer Science, Maths, Machine Learning, Data Science, or related field.
  • Experience with MLOps pipelines, model deployment, or production ML systems.
  • Familiarity with performance analysis, profiling tools, or numerical accuracy validation.
  • Exposure to distributed training or inference systems.
  • Experience with hardware‑accelerated ML, compilers, or system‑level performance considerations.
  • Familiarity with CI/CD systems used for ML workflows.
  • Experience contributing to open‑source ML frameworks or tooling.

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection.

We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support).

We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar!

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.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications.

We take pride in our commitment to creating an inclusive and diverse workplace.

As part of our recruitment process, we ask for confidential diversity data from all applicants.

This data will be anonymised so that no personal identification information will be collected, and is retained for statistical purposes only and is not attached to your application.

Your responses to the following three questions will remain confidential and will not impact or be used in any way in regards to your application.

We are only using this data to improve our hiring process to be inclusive of all diversity backgrounds.

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Staff Engineer (ML Engineer) in London employer: Cerebras

Graphcore is an exceptional employer located in the vibrant city of Bristol, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from competitive salaries, flexible working arrangements, and generous leave policies, alongside opportunities for professional growth in cutting-edge AI technology. With a focus on employee well-being, including private medical insurance, Graphcore stands out as a rewarding place to build a meaningful career.

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Contact Details:

Cerebras Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Engineer (ML Engineer) in London

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Cerebras or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Cerebras.

Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Cerebras.

Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Cerebras that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Staff Engineer (ML Engineer) in London

Machine Learning Systems
AI Concepts
Model Behaviour
Performance Testing
Reliability Testing
Correctness Validation
ML Frameworks (e.g. PyTorch, TensorFlow, JAX)

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Cerebras.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Cerebras and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Cerebras

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Cerebras uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.