At a Glance
- Tasks: Join a team to optimise AI applications and influence hardware decisions.
- Company: CommonAI CIC, a non-profit focused on collaborative AI development.
- Benefits: Competitive salary, pension, professional growth, and networking opportunities.
- Other info: Vibrant office near Cambridge station with a supportive work culture.
- Why this job: Make a real impact in the AI field while working with cutting-edge technology.
- Qualifications: Degree in computer science or related field; experience in performance modelling and optimisation.
The predicted salary is between 50000 - 65000 € per year.
CommonAI CIC is a non‑profit membership organisation, founded on a belief in collaborative engineering for the safe and responsible development of foundational AI technologies. A place where AI startups, enterprises large and small, public sector bodies and academia can share resources and knowledge to codevelop and grow businesses, fast.
We are seeking a Performance Engineer to join our rapidly growing team. In this role, you will work with AI researchers and software engineers to build up a detailed understanding of how their applications are performing. You will instrument and collect granular metrics from inference and training jobs and use that information to develop sophisticated mathematical models that predict how software optimisations and architectural or hardware changes will impact system performance. Your work will directly influence both our in‑house and member's hardware purchasing decisions and architectural optimisations, ensuring teams can run AI workloads efficiently and cost‑effectively.
Requirements
- Degree in computer science, mathematics or an adjacent field.
- Experience building insightful mathematical models and performance calculators (Excel/Google Sheets or Python modelling experience) to forecast system behaviour.
- Optimisation of code running on GPUs and/or other accelerators (e.g., CUDA).
- Solid understanding of computer architecture fundamentals and how LLMs and Deep Learning models execute on that hardware (inference vs. training, matrix multiplication, KV‑caching, etc.).
- Proficiency with profiling tools (NVIDIA Nsight, PyTorch Profiler) and monitoring stacks (Prometheus, Grafana).
- Capability to work in Python for data analysis (Pandas, NumPy) and scripting.
Highly Valued Qualifications
- Post‑graduate degrees and research experience in relevant fields (please list your publications).
- Deep understanding of inference serving frameworks (e.g., vLLM).
- Background in statistical analysis.
- Contributions to open source and/or research projects.
Benefits
- A collaborative and supportive work environment.
- The opportunity to have a high impact in a growing organisation.
- Competitive salary package and pension.
- Professional development opportunities.
- Networking opportunities with influential people from across the tech sector and academia.
- A vibrant office environment located a few minutes' walk away from Cambridge train station.
Performance Engineer employer: CommonAI CIC
CommonAI CIC is an exceptional employer that fosters a collaborative and supportive work environment, ideal for those passionate about AI technology. With a vibrant office just minutes from Cambridge train station, employees benefit from competitive salaries, professional development opportunities, and the chance to network with influential figures in the tech sector and academia. Joining our team as a Performance Engineer means making a significant impact in a rapidly growing organisation dedicated to the responsible development of foundational AI technologies.
StudySmarter Expert Advice🤫
We think this is how you could land Performance Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the AI and performance engineering space. Attend meetups, webinars, or even just grab a coffee with someone in the field. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your mathematical models and performance calculators. Share your projects on GitHub or personal websites. This gives potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with profiling tools and optimisation techniques. Practise explaining complex concepts in simple terms – it shows you really understand your stuff!
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to highlight how your skills align with our mission at CommonAI CIC. Let’s make AI better together!
We think you need these skills to ace Performance Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in building mathematical models and optimising code for GPUs. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about performance engineering and how your background fits with our mission at CommonAI. Let us know what excites you about working with AI technologies.
Showcase Your Technical Skills:Don’t forget to mention your proficiency with tools like NVIDIA Nsight and PyTorch Profiler. We love seeing candidates who can demonstrate their technical prowess, so include any relevant experiences that highlight your capabilities.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at CommonAI CIC
✨Know Your Stuff
Make sure you brush up on your knowledge of computer architecture and performance metrics. Familiarise yourself with the specific tools mentioned in the job description, like NVIDIA Nsight and Prometheus. Being able to discuss how these tools can help optimise AI workloads will show that you're serious about the role.
✨Show Off Your Modelling Skills
Prepare to talk about your experience with mathematical models and performance calculators. Bring examples of your work, whether it's in Excel, Google Sheets, or Python. If you can demonstrate how you've used these skills to forecast system behaviour in the past, it’ll definitely impress the interviewers.
✨Get Technical with Examples
Be ready to dive deep into technical discussions. Think of specific instances where you've optimised code for GPUs or worked with deep learning models. Sharing concrete examples of your problem-solving process will highlight your expertise and make you stand out.
✨Ask Insightful Questions
Interviews are a two-way street, so prepare some thoughtful questions about the team’s current projects or challenges they face. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you. Plus, it gives you a chance to showcase your knowledge about AI technologies!
