At a Glance
- Tasks: Build performance models to optimise AI infrastructure and influence real-world decisions.
- Company: Innovative non-profit in Cambridge focused on AI efficiency.
- Benefits: Competitive salary, pension, hybrid work, and exposure to the AI community.
- Other info: Early-stage role with significant growth potential and collaboration opportunities.
- Why this job: Join a mission-driven team making impactful changes in AI infrastructure.
- Qualifications: Degree in computer science or related field; experience in performance modelling and GPU optimisation.
The predicted salary is between 80100 - 97900 £ per year.
Nobody quite knows where their compute budget is actually going until someone builds the model that tells them. That's this role. My client is a Cambridge-based non-profit that exists to stop different parts of the AI world quietly rebuilding the same infrastructure. Rather than a startup, a big enterprise, a government department and a university lab each working out GPU efficiency from scratch, they pool the hard problems and the expertise needed to solve them, so everyone moves faster. It's early days for the organisation but there's serious momentum and serious financial backing behind it already.
They're hiring Performance Engineers at junior and senior level, to sit at the sharp end of that mission.
Day to day
You'd sit between the research and engineering teams, pulling real numbers off live training and inference runs rather than working from theory. From there, the job is building the models and calculators that turn those numbers into an actual answer: will this optimisation help, would a different accelerator be worth the spend, is this architecture change going to pay for itself. Those answers don't stay internal either, they shape what gets bought and how systems get built, for the organisation itself and for everyone else in the membership relying on that judgement.
What you'll bring
- A degree in computer science, mathematics, or something adjacent
- A track record of building performance models or calculators (Python or spreadsheet-based) that actually forecast how a system will behave
- Hands-on GPU/accelerator code optimisation, CUDA or similar
- Genuine understanding of how LLMs and deep learning models run on real hardware, training versus inference, matrix multiplication, KV-caching, that level of detail
- Comfortable in profiling tools like Nsight or PyTorch Profiler, and monitoring stacks like Prometheus and Grafana
- Python for data work, Pandas and NumPy, plus general scripting
Nice to have rather than essential:
- A postgraduate degree and research background (publications welcome)
- Real depth on inference serving frameworks like vLLM
- A stats background
- Any open source or research contributions
Why look twice at this one
It's a rare early seat at something with genuine backing and genuine ambition, where the work you do gets acted on rather than filed away. Competitive salary and pension, hybrid from a Cambridge office, and real exposure to people across the wider AI and academic scene.
Senior Performance Engineer | AI Infrastructure | Cambridge (Hybrid) employer: Pure Resourcing Solutions Limited
Join a leading manufacturer in the construction materials sector that prioritises employee wellbeing and development. With a strong commitment to training, including full Microsoft certification support, and a culture that values people, you will thrive in an environment recognised for its Investors in People Platinum status. This role not only offers competitive benefits but also the chance to work on innovative digital solutions in a collaborative team setting in Ipswich.
Contact Details:
Pure Resourcing Solutions Limited Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior Performance Engineer | AI Infrastructure | Cambridge (Hybrid)
✨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 Pure Resourcing Solutions Limited 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 Pure Resourcing Solutions Limited.
✨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 Pure Resourcing Solutions Limited.
✨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 Pure Resourcing Solutions Limited 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 Senior Performance Engineer | AI Infrastructure | Cambridge (Hybrid)
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 Pure Resourcing Solutions Limited.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Pure Resourcing Solutions Limited 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 Pure Resourcing Solutions Limited
✨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 Pure Resourcing Solutions Limited 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.
