At a Glance
- Tasks: Build predictive models for AI infrastructure and optimise performance metrics.
- Company: Innovative non-profit in Cambridge, uniting AI startups and researchers.
- Benefits: Competitive salary, pension, hybrid work, and exposure to the AI community.
- Other info: Dynamic environment with opportunities to influence cutting-edge AI projects.
- Why this job: Kickstart your career with real ownership and mentorship from senior engineers.
- Qualifications: PhD or exceptional master's in computer science, mathematics, or related fields.
The predicted salary is between 63000 - 77000 £ per year.
Most engineers find out whether a change works after it ships. This role is about knowing before anyone spends a penny on new hardware, building the models that predict it.
My client is a Cambridge-based non-profit built on a fairly simple premise: different bits of the AI world keep solving the same infrastructure problems separately, and that’s wasteful. So they’ve built a shared space where startups, big enterprises, government bodies and university researchers can pool that hard technical work instead. Early days as an organisation, but real backing and real momentum behind it.
This particular seat is for an early career professional. We’re after someone academically exceptional, ideally with a PhD, who’s ready to get stuck into real technical work quickly rather than needing a long runway to get there.
Day to day:
- You’d work alongside senior engineers on the team, pulling real metrics off live training and inference jobs and turning them into models and calculators that answer actual questions, whether an optimisation is worth shipping, whether a different setup would run cheaper. Real ownership early, with senior support close by.
What you’ll bring:
- A postgraduate research background, ideally a PhD in computer science, mathematics, physics or a closely related field, strongly preferred; exceptional recent master’s graduates with directly relevant coursework will also be considered.
- A genuine, demonstrated grasp of computer architecture fundamentals and how LLMs and deep learning models actually run on hardware, training versus inference, matrix multiplication, KV-caching.
- Real experience building performance models or forecasting tools, Python or spreadsheet-based, from research, a thesis, a placement, or serious personal projects.
- Hands-on work with GPU or accelerator code, CUDA or similar.
- Familiarity with profiling tools (Nsight, PyTorch Profiler) and ideally some exposure to monitoring stacks (Prometheus, Grafana).
- Strong Python for data work, Pandas and NumPy, genuine scripting ability.
Nice to have:
- Exposure to inference serving frameworks like vLLM, published research, or open source contributions in this space.
Why look twice at this one:
An early route into industry for someone whose academic record speaks for itself, working directly with senior engineers on problems with real backing behind them. Pension, hybrid from a Cambridge office, and exposure to people across the wider AI and academic scene most people this early in their career don’t get.
Performance Engineer (Junior) | 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 Performance Engineer (Junior) | 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 Performance Engineer (Junior) | 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.
