Staff Engineer (ML Engineer)

EngineersOfAI; Cambridge; On-site; GBP 50,000 - 80,000; Full time

Benefits offered by this job

Unlimited annual leave

Up to 5% matched pension

Phantom equity

Flexible work environment

Free food and barista services

Health cash plan

Income protection

Life assurance

Job summary

EngineersOfAI is searching for a Machine Learning Validator in Cambridge, UK. The chosen candidate will validate complex ML systems and ensure they run reliably on advanced infrastructure.

The role requires strong experience in ML software engineering, debugging in Linux, and proficiency in Python. Additional benefits include unlimited annual leave, a matched pension scheme, and equity shares, ensuring a robust work-life balance.

Qualifications

• Experience in Machine Learning or similar software engineering roles.
• Understanding of performance trade-offs in ML models.
• Skilled in automation and benchmarking.

Responsibilities

• Validate ML systems before customer release.
• Run open source models and build benchmarking pipelines.
• Debug model behavior and report system performance.

Skills

Machine Learning experience

Neural networks knowledge

Hands-on with ML frameworks

Strong Python skills

Debugging skills in Linux

Tools

PyTorch

TensorFlow

JAX

Job description

About the job

Validate the ML stack that turns accelerator hardware into trusted AI performance.

This role sits where modern ML models meet Graphcore’s software and hardware stack. You will test, benchmark and validate complex systems before they reach customers.

Your work will expose regressions, correctness issues and performance limits across frameworks, models and execution environments. You will help teams understand what is working, what is breaking and why.

You will run open source models, build automated benchmarking pipelines and create targeted tests for low level ML behaviour. That includes numerical precision, quantisation, attention mechanisms, distributed execution and model subgraphs.

This is a role for someone who wants to stay close to how AI systems really work. You will not design new models, but you will make them run reliably on ambitious infrastructure.

The team and culture

The ML QA team is where Graphcore’s ML software stack comes together for validation. Work spans unit tests, full model benchmarks, distributed workloads, simulators, emulators and hardware targets.

Engineers are expected to take ownership, question assumptions and improve how testing is done. The team moves quickly, but decisions are grounded in evidence, benchmark data and technical discussion.

You will work closely with software, infrastructure and hardware teams. Squads organise around priorities, with space for engineers to shape roadmaps and raise the quality bar.

What we’re looking for

• Strong experience in Machine Learning or ML-adjacent software engineering roles.
• A solid grasp of neural networks, training, inference, numerical precision and performance trade-offs.
• Hands-on experience with PyTorch, TensorFlow, JAX, Triton or similar ML frameworks and tools.
• Strong Python skills for automation, experimentation, benchmarking and reporting.
• Experience designing, running and analysing ML benchmarks or model experiments.
• Confident debugging skills in Linux, with curiosity about model behaviour and system performance.

Benefits

• Unlimited annual leave
• Up to 5% matched pension
• Phantom equity - share in Graphcore's success
• True flexibility in how and where you work
• Office spaces designed for collaboration
• Free food and an on-site barista
• Health cash plan
• Income protection
• Life assurance
• Along with other benefits you can choose from (private medical insurance, dental plan etc)

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.