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For Companies At a Glance
- Tasks: Create and own analytical models for cutting-edge optical processors in AI.
- Company: Join Flux Computing, a leader in optical computing innovation.
- Benefits: Competitive salary, stock options, full healthcare, and flexible work arrangements.
- Why this job: Make a real impact on AI technology while working with a talented team.
- Qualifications: 5+ years in performance modelling; strong C++ and Python skills required.
- Other info: Enjoy chef-cooked dinners, monthly socials, and access to high-spec tech.
The predicted salary is between 130000 - 200000 ÂŁ per year.
Flux Computing designs and manufactures optical processors to train and run inference on large AI models. Join us to be part of a highly motivated and skilled team that thrives on delivering impact and innovation at speed.
The Role
We’re searching for a Senior Performance Modelling Engineer to create and own the analytical and simulation models that steer OTPU architecture and software evolution. You will build functional simulators as well as high-fidelity, cycle-accurate models of our optical compute system. This role is critical to explore “what-if” design spaces, and deliver insights that directly influence our software, hardware, and optical roadmaps. This role sits at the crossroads of hardware architecture, software tooling and machine-learning workload analysis, perfect for an engineer who loves data-driven decision-making and fast iteration.
Responsibilities
- Project Ownership: Own and deliver projects on your team\’s roadmap that unlock key high-impact technical and business milestones that drive the success of Flux.
- Collaboration: Work shoulder-to-shoulder with hardware, compiler and ML framework teams to ensure models reflect reality and reality meets performance goals.
- Functional Simulator: Design, build, and maintain a functional simulator of the OPTU subsystem and full pipeline.
- Performance Simulator: Design and maintain architectural & cycle-accurate models of the OPTU subsystems and pipeline. Identify throughput, latency and utilisation hot-spots; propose architectural, or scheduling fixes.
- Workload Analysis & Bottleneck Hunting: Instrument benchmarks (LLMs, diffusion, graph workloads) to collect detailed traces.
- Design-Space Exploration: Run massive parameter sweeps with your functional and to understand tradeoffs and guide the software, hardware, and optical teams. Package results into clear, quantitative analyses and design recommendations.
- Tooling & Automation: Develop Python/C++ tooling for trace parsing, statistical analysis and visualisation. Integrate models into CI so that every RTL commit gets a performance smoke test.
Skills & Experience
- 5+ years building performance or power models for CPUs, GPUs, ASICs, or accelerators.
- Strong coding ability in C++ and Python; experience with discrete-event or cycle-accurate simulators (e.g., gem5, SystemC, custom in-house).
- Solid grasp of computer-architecture fundamentals: memory systems, interconnects, queuing theory, Amdahl/Gustafson analysis.
- Familiarity with machine-learning workloads and common frameworks (PyTorch, TensorFlow, JAX).
- Comfort reading RTL or schematics and discussing micro-architectural trade-offs with hardware designers.
- Excellent data-visualisation and communication skills: able to turn millions of simulation samples into one decisive slide.
- Bachelor’s+ in EE, CS, Physics, Applied Maths or related; advanced degree preferred but not required.
- Personal or open-source projects in simulators, ML kernels, or performance analysis are a significant plus.
Compensation & Benefits
- £153,000 – £187,000 annual salary, depending on experience, skills, and location.
- Competitive stock options, you’re not just part of the journey, you will own a piece of it.
- Work from our HQ in King’s Cross, right in the middle of London’s buzzing AI scene.
- Live within 45 minutes of the office? Perfect. Live within 20 minutes? We’ll add an extra location bonus to your salary.
- We offer visa sponsorship and full relocation support (UK and abroad), through a dedicated third-party provider who are on hand to make your move to London as seamless as possible.
- Full BUPA healthcare and dental cover, medical history disregarded.
- High-spec tech for everyone – M4 Macs as standard, M4 Pros for Engineers.
- Sony noise-cancelling headphones and ergonomic setups to keep you comfortable and focused.
- Personal company card to spend on tools that help you do your job – like ChatGPT Pro or anything else that boosts your workflow.
- Healthy, chef-cooked dinners in the office every night, with something for every diet and tastebud.
- Monthly off-site team socials.
- 25 days of paid holiday, plus all the UK bank holidays.
- Access to our in-house 3D printer for personal or work projects.
- Cycle2work scheme.
- Need a caffeine fix? We’ve got you covered with a tab at our favourite local coffee shop.
- We offer a pension plan and salary sacrifice options.
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AI Senior Performance Modeller employer: Flux Computing
Contact Detail:
Flux Computing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Senior Performance Modeller
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Flux Computing. A personal introduction can make all the difference when it comes to landing that interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to performance modelling or machine learning. This is your chance to demonstrate your coding prowess in C++ and Python, so make it shine!
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of computer architecture and simulation tools. Practice explaining complex concepts clearly, as communication is key in this role. We want to see how you can turn data into actionable insights!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of the Flux team. Don’t miss out on this opportunity!
We think you need these skills to ace AI Senior Performance Modeller
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let us see your enthusiasm for AI and performance modelling. Share any personal projects or experiences that highlight your love for the field – it really helps us get to know you!
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter to reflect the skills and experiences mentioned in the job description. We want to see how your background aligns with what we're looking for, so don’t hold back on the details!
Highlight Collaboration Skills: Since this role involves working closely with various teams, emphasise your collaboration skills in your application. Share examples of how you've successfully worked with others to achieve common goals – we love a team player!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining our team at Flux Computing!
How to prepare for a job interview at Flux Computing
✨Know Your Models Inside Out
Make sure you’re well-versed in the performance and power models relevant to CPUs, GPUs, and ASICs. Be ready to discuss your experience with cycle-accurate simulators like gem5 or SystemC, as well as any personal projects that showcase your skills.
✨Showcase Your Collaboration Skills
Flux Computing values teamwork, so prepare examples of how you've worked closely with hardware, compiler, and ML framework teams. Highlight specific instances where your collaboration led to successful project outcomes or innovative solutions.
✨Prepare for Technical Questions
Expect deep dives into computer architecture fundamentals and machine-learning workloads. Brush up on topics like memory systems, queuing theory, and Amdahl/Gustafson analysis, and be ready to explain complex concepts in a clear and concise manner.
✨Visualise Your Data
Since excellent data visualisation is key for this role, practice turning complex simulation results into straightforward insights. Prepare a few slides or examples that demonstrate how you can distil large amounts of data into actionable recommendations.
