Senior Performance Modeling Engineer
Senior Performance Modeling Engineer

Senior Performance Modeling Engineer

Slough Full-Time 48000 - 84000 £ / year (est.) No home office possible
Go Premium
F

At a Glance

  • Tasks: Create and own analytical models for optical processors in AI.
  • Company: Flux Computing designs cutting-edge optical processors for large AI models.
  • Benefits: Competitive salary, stock options, healthcare, and 25 days PTO.
  • Why this job: Join a dynamic team driving innovation in AI with impactful projects.
  • Qualifications: 5+ years in performance modeling; strong C++ and Python skills required.
  • Other info: Work from our vibrant Kings Cross office; extra incentives for short commutes.

The predicted salary is between 48000 - 84000 £ per year.

Company Overview

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.

The Role

We’re searching for a Performance Modeling 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

  • 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.

F

Contact Detail:

Flux Computing Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Senior Performance Modeling Engineer

Tip Number 1

Familiarise yourself with the latest trends in optical computing and AI models. Understanding the current landscape will help you engage in meaningful conversations during interviews and demonstrate your passion for the field.

Tip Number 2

Network with professionals in the optical computing and performance modelling sectors. Attend relevant meetups or conferences in London to connect with potential colleagues and learn more about the challenges they face, which can give you an edge in discussions.

Tip Number 3

Showcase any personal or open-source projects related to simulators or performance analysis on platforms like GitHub. This not only highlights your skills but also demonstrates your initiative and commitment to the field.

Tip Number 4

Prepare to discuss specific examples of how you've used data-driven decision-making in past projects. Being able to articulate your thought process and the impact of your work will resonate well with the interviewers at Flux.

We think you need these skills to ace Senior Performance Modeling Engineer

Performance Modeling
C++ Programming
Python Programming
Discrete-Event Simulation
Cycle-Accurate Simulation
Computer Architecture Fundamentals
Memory Systems Knowledge
Interconnects Understanding
Queuing Theory
Amdahl/Gustafson Analysis
Machine Learning Workload Familiarity
PyTorch Experience
TensorFlow Experience
JAX Knowledge
RTL Reading Skills
Micro-Architectural Trade-off Discussion
Data Visualisation Skills
Analytical Skills
Collaboration Skills
Project Ownership
Tooling and Automation Development

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in performance modeling, coding skills in C++ and Python, and familiarity with machine-learning workloads. Use specific examples that demonstrate your ability to build functional simulators and analyse workloads.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and your understanding of the role. Mention how your background aligns with Flux Computing's goals and how you can contribute to their projects. Be sure to include any personal or open-source projects that relate to the position.

Highlight Collaboration Skills: Since the role involves working closely with hardware, compiler, and ML framework teams, emphasise your collaboration skills. Provide examples of past projects where you successfully worked in a team environment to achieve technical milestones.

Showcase Data-Driven Decision Making: Demonstrate your ability to make data-driven decisions by including examples of how you've used analytical models or simulations in previous roles. Discuss any tools or methodologies you employed to guide architectural or scheduling fixes based on your analyses.

How to prepare for a job interview at Flux Computing

Showcase Your Technical Skills

Be prepared to discuss your experience with performance or power models, especially for CPUs, GPUs, and ASICs. Highlight specific projects where you used C++ and Python, and be ready to explain your approach to building simulators.

Demonstrate Collaboration Experience

Flux Computing values teamwork, so share examples of how you've worked closely with hardware, compiler, and ML framework teams. Discuss any challenges you faced and how you overcame them through collaboration.

Prepare for Design-Space Exploration Questions

Expect questions about your experience with design-space exploration and workload analysis. Be ready to discuss how you've run parameter sweeps and the insights you derived from them that influenced design decisions.

Communicate Clearly and Effectively

Since excellent communication skills are crucial, practice summarising complex data into clear, concise insights. Prepare a few examples of how you've turned extensive simulation results into actionable recommendations.

Senior Performance Modeling Engineer
Flux Computing
Location: Slough
Go Premium

Land your dream job quicker with Premium

You’re marked as a top applicant with our partner companies
Individual CV and cover letter feedback including tailoring to specific job roles
Be among the first applications for new jobs with our AI application
1:1 support and career advice from our career coaches
Go Premium

Money-back if you don't land a job in 6-months

F
  • Senior Performance Modeling Engineer

    Slough
    Full-Time
    48000 - 84000 £ / year (est.)
  • F

    Flux Computing

    50-100
Similar positions in other companies
UK’s top job board for Gen Z
discover-jobs-cta
Discover now
>