At a Glance
- Tasks: Quantify AI performance and model real-world metrics to drive impactful decisions.
- Company: Mission-driven organisation at the forefront of AI infrastructure.
- Benefits: Competitive salary, pension, and hybrid work from our Cambridge office.
- Other info: Collaborative environment with opportunities to influence the broader AI ecosystem.
- Why this job: Shape the future of AI with data-driven insights and innovative solutions.
- Qualifications: Degree in computer science or related field; experience in performance modelling and GPU optimisation.
The predicted salary is between 59400 - 72600 £ per year.
In this role you will quantify and model the real-world performance of AI training and inference to answer whether optimisations or different accelerators pay off. You’ll sit between research and engineering to translate live data into actionable insights that influence buying decisions and system design. You’ll work on models and calculators that forecast hardware efficiency at scale, contributing to a mission-driven, well-backed organisation accelerating AI progress. This is a rare opportunity to shape infrastructure decisions that benefit the broader AI ecosystem.
Pay / Benefits
Competitive salary, pension, hybrid from Cambridge office.
Responsibilities
- Bridge research and engineering to extract live training/inference metrics.
- Build performance models and calculators to forecast system behaviour and cost/benefit of optimisations.
- Assess whether architecture changes or accelerators deliver ROI and inform procurement and system design.
- Shape decisions that affect the organisation and its members through data-driven insights.
Key requirements
- Degree in computer science, mathematics, or adjacent field.
- Experience building performance models or calculators that forecast system behaviour.
- Hands-on GPU/accelerator code optimisation (CUDA or similar).
- Strong understanding of how LLMs and DL models run on hardware (training vs inference, matrix multiplication, KV-caching).
- Familiarity with profiling tools (Nsight, PyTorch Profiler) and monitoring stacks (Prometheus, Grafana).
- Python for data work (Pandas, NumPy) and scripting.
- Collaboration across research, engineering, and operations.
- Analytical mindset with attention to detail.
- Ability to translate data findings into actionable decisions.
Senior Performance Engineer | AI Infrastructure | Cambridge (Hybrid) | employer: Pure Resourcing Solutions
Join a forward-thinking professional services business that champions a modern approach to finance and advisory, offering a vibrant work culture where your insights truly matter. With flexible and hybrid working options, you'll have the chance to influence decision-making for a diverse portfolio of entrepreneurial clients while enjoying clear development opportunities in a supportive environment. This is an excellent employer for those seeking meaningful work that goes beyond traditional accountancy, fostering both personal and professional growth.
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 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.
✨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.
✨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 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.
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 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
✨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 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.
