Senior ML Engineer

Senior ML Engineer

Full-Time 70000 - 90000 £ / 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 medical insurance, and a vibrant office culture.
  • Other info: Inclusive workplace with opportunities for growth and innovation in cutting-edge AI technology.
  • Why this job: Make a real impact in AI while collaborating with top experts in a dynamic environment.
  • Qualifications: 6+ years in ML engineering, strong Python skills, and experience with major ML frameworks required.

The predicted salary is between 70000 - 90000 £ per year.

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 datacentre 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

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 ML QA 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

Essential:

  • 6+ years of 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 PyTorch, TensorFlow, 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/PhD or equivalent experience in Computer Science, Maths, Machine Learning, Data Science, or related field.

Desirable:

  • 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.

Benefits

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.

Senior ML Engineer employer: Cerebras

Graphcore is an exceptional employer, offering a dynamic work environment in the heart of Bristol where innovation thrives. With a strong focus on employee growth, we provide extensive benefits including flexible working arrangements, generous leave policies, and comprehensive health plans, all while fostering a culture of inclusivity and collaboration among some of the brightest minds in AI. Join us to make a meaningful impact in the rapidly evolving field of artificial intelligence, backed by the resources of the SoftBank Group.
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Contact Detail:

Cerebras Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Senior ML Engineer

✨Tip Number 1

Network like a pro! Reach out to current employees at Graphcore on LinkedIn or other platforms. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.

✨Tip Number 2

Prepare for the technical interview by brushing up on your ML frameworks and debugging skills. Practice explaining complex concepts in simple terms, as you'll want to showcase your expertise while being approachable.

✨Tip Number 3

Showcase your passion for AI! During interviews, share your personal projects or contributions to open-source ML frameworks. This not only highlights your skills but also demonstrates your commitment to the field.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Graphcore team.

We think you need these skills to ace Senior ML Engineer

Machine Learning Systems
AI Concepts
Model Behaviour
Benchmarking
Performance Analysis
Reliability Testing
ML Frameworks (e.g. PyTorch, TensorFlow, JAX)
Python Programming
Automated Testing
Debugging Skills
Linux Environments
MLOps Pipelines
Distributed Training
CI/CD Systems

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights your experience with machine learning systems and frameworks. We want to see how your skills align with the role, so don’t be shy about showcasing your hands-on experience and any relevant projects you've worked on.

Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for the Senior ML Engineer role. Share your passion for AI and how your background in debugging and performance analysis can contribute to our team’s success.

Showcase Your Technical Skills: When applying, make sure to mention your proficiency in Python and any major ML frameworks like PyTorch or TensorFlow. We love seeing candidates who can demonstrate their technical expertise and problem-solving abilities.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and helps us keep track of all the amazing talent interested in joining our team!

How to prepare for a job interview at Cerebras

✨Know Your ML Frameworks

Make sure you’re well-versed in the major ML frameworks like PyTorch and TensorFlow. Brush up on their functionalities, strengths, and weaknesses, as you might be asked to discuss how you’ve used them in past projects.

✨Showcase Your Debugging Skills

Prepare to talk about specific instances where you identified and resolved performance issues in ML systems. Be ready to explain your thought process and the tools you used for debugging.

✨Understand AI Concepts Deeply

Since the role requires a solid understanding of core AI concepts, make sure you can explain neural networks, training vs inference, and performance trade-offs clearly. Use examples from your experience to illustrate your points.

✨Prepare for Hands-On Testing Scenarios

Expect practical questions or scenarios where you’ll need to demonstrate your ability to build and maintain automated testing pipelines. Familiarise yourself with the types of tests you might run and how to analyse the results effectively.

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