At a Glance
- Tasks: Create and own analytical models for optical processors in AI.
- Company: Flux Computing designs innovative optical processors for large AI models.
- Benefits: Competitive salary, stock options, healthcare, and 25 days PTO.
- Why this job: Join a dynamic team shaping the future of computing with cutting-edge technology.
- Qualifications: 7+ years in performance modelling; strong C++ and Python skills required.
- Other info: Work from our Kings Cross HQ; extra £24,000/year for short commutes.
The predicted salary is between 43200 - 72000 £ per year.
Flux Computing designs and manufactures optical processors to train and run inference on large AI models. Join us in London to be part of a highly motivated and skilled team that thrives on delivering impact and innovation at speed.
We’re searching for a Staff 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
- Ownership: Define and deliver the technical vision and roadmap for your team that unlocks key strategic technical and business goals that are essential to the success of Flux.
- Collaboration: Partner closely with all engineering teams to help shape our overall system architecture and delivery while ensuring models reflect reality and reality meets performance goals.
- Champion Modelling: Educate peers on modelling methodology and champion data-driven design culture.
- 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.
- 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
- 7+ years building performance or power models for CPUs, GPUs, ASICs, or accelerators.
- Proven track record providing technical leadership to a team of 5~10 engineers, resulting in significant business impact.
- Strong coding ability in C++ and Python; experience with discrete-event or cycle-accurate simulators (e.g., gem5, SystemC, custom in-house).
- Strong 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
- Competitive salary and stock options in a rapidly growing AI company.
- Based in our new 5,000 sq. ft. office in the AI hub of Kings Cross, London.
- To foster collaboration in our high-growth environment, we require all employees to work from our London HQ and live within a 45-minute commute. We offer an extra £24,000/year incentive for those living within 20 minutes.
- Comprehensive healthcare insurance.
- 25 days PTO policy plus bank holidays.
- Private access to our in-house 3D printer.
If you are passionate about pushing the boundaries of what's possible in AI and thrive in a high-energy, fast-paced environment, we want to hear from you. Apply now to join Flux and be a key player in shaping the future of computing.
Staff Performance Modelling Engineer employer: Flux Computing
Contact Detail:
Flux Computing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Performance Modelling Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in optical computing and AI models. Understanding the specific technologies and methodologies used by Flux Computing will help you engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your experience with performance modelling tools and techniques. Be prepared to discuss specific projects where you've built or improved performance models, especially in relation to CPUs, GPUs, or ASICs.
✨Tip Number 3
Network with professionals in the field of optical computing and performance modelling. Attend relevant meetups or conferences to connect with potential colleagues and gain insights that could be beneficial for your application.
✨Tip Number 4
Prepare to demonstrate your coding skills in C++ and Python. Consider working on a small project or contributing to open-source initiatives that highlight your ability to develop simulation tools or performance analysis frameworks.
We think you need these skills to ace Staff Performance Modelling Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in performance modelling, coding skills in C++ and Python, and any familiarity with machine-learning workloads. Use specific examples that demonstrate your technical leadership and impact.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your background aligns with the responsibilities of the Staff Performance Modelling Engineer role. Mention your experience with simulation models and your approach to data-driven decision-making.
Showcase Relevant Projects: If you have personal or open-source projects related to simulators, ML kernels, or performance analysis, be sure to mention them. This can set you apart and show your hands-on experience in the field.
Prepare for Technical Questions: Anticipate technical questions related to computer architecture fundamentals and performance modelling. Brush up on concepts like memory systems, queuing theory, and architectural trade-offs to demonstrate your expertise during interviews.
How to prepare for a job interview at Flux Computing
✨Understand the Role
Make sure you have a solid grasp of what a Staff Performance Modelling Engineer does. Familiarise yourself with performance modelling, simulation techniques, and how they apply to optical computing. This will help you answer questions confidently and demonstrate your enthusiasm for the role.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with C++ and Python, as well as any relevant projects involving discrete-event or cycle-accurate simulators. Bring examples of your work that highlight your coding ability and understanding of computer architecture fundamentals.
✨Prepare for Collaboration Questions
Since collaboration is key in this role, think of examples where you've successfully worked with cross-functional teams. Be ready to discuss how you’ve influenced system architecture and ensured that models align with performance goals.
✨Demonstrate Data-Driven Decision Making
Flux Computing values data-driven insights, so be prepared to talk about how you've used data analysis in past projects. Discuss any experience you have with workload analysis, bottleneck hunting, or design-space exploration to show your analytical mindset.