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For Companies At a Glance
- Tasks: Design and own analytical models for cutting-edge optical compute systems.
- Company: Join a pioneering team revolutionising AI with innovative optical processors.
- Benefits: Enjoy flexible work options, competitive salary, and opportunities for rapid career growth.
- Why this job: Be at the forefront of AI technology, collaborating with top engineers in a dynamic environment.
- Qualifications: 5+ years in performance modelling; proficiency in C++ and Python required.
- Other info: Ideal for those passionate about hardware, software, and machine learning.
The predicted salary is between 48000 - 84000 £ per year.
Job Description
Build the Future of AI with Optical Compute
We're pioneering optical processors to train and run inference on large-scale AI models. Join a team of highly motivated and skilled engineers dedicated to rapid innovation and high-impact outcomes.
The Role: Senior Performance Modelling Engineer
We're looking for a Senior Performance Modelling Engineer to design and own the analytical and simulation models that guide the evolution of our Optical TPU (OTPU) architecture and software. You will be instrumental in building functional and high-fidelity, cycle-accurate models of our optical compute system.
This is a high-leverage role that sits at the intersection of hardware design, software tooling, and machine learning workloads-ideal for engineers who thrive on data-driven decisions, rapid iteration, and solving complex performance challenges.
Key Responsibilities
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End-to-End Ownership: Lead and deliver critical projects that enable major technical and business milestones.
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Cross-Functional Collaboration: Work closely with hardware, compiler, and ML framework teams to ensure performance models are both accurate and actionable.
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Simulator Development:
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Build and maintain a functional simulator of the OTPU pipeline and subsystems.
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Develop architectural and cycle-accurate simulators to identify bottlenecks and optimize throughput, latency, and utilization.
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Benchmarking & Bottleneck Analysis: Instrument LLMs, diffusion models, and graph workloads to generate detailed traces for deep performance analysis.
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Design-Space Exploration: Run extensive parameter sweeps to explore architectural tradeoffs, and deliver clear, quantitative insights that guide our hardware, software, and optical designs.
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Tooling & Automation: Create robust Python/C++ tools for trace parsing, statistical analysis, and visualization. Integrate models into CI pipelines for automated performance regression testing.
Required Skills & Experience
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5+ years of experience building performance or power models for CPUs, GPUs, ASICs, or custom accelerators.
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Proficiency in C++ and Python, with hands-on experience in developing discrete-event or cycle-accurate simulators (eg, gem5, SystemC, or custom tools).
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Strong understanding of computer architecture fundamentals: memory systems, interconnects, queuing theory, Amdahl's and Gustafson's laws.
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Familiarity with machine learning workloads and frameworks like PyTorch, TensorFlow, or JAX.
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Ability to interpret RTL/schematics and discuss micro-architectural trade-offs with hardware engineers.
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Excellent data visualization and communication skills – capable of distilling millions of simulation samples into a single, decisive insight.
Preferred Qualifications
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Advanced degree (Master's or PhD) in Electrical Engineering, Computer Science, Physics, Applied Math, or a related field.
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Open-source or personal projects involving simulators, ML kernels, or performance analysis.
This role offers a unique opportunity to shape the direction of optical compute at a foundational level. If you're excited to work at the cutting edge of hardware, software, and AI, we'd love to hear from you.
Modelling Engineer (Mid-Staff) employer: La Fosse Associates Limited
Contact Detail:
La Fosse Associates Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Modelling Engineer (Mid-Staff)
✨Tip Number 1
Familiarise yourself with the latest advancements in optical computing and performance modelling. Understanding the current trends and technologies will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Engage with online communities or forums related to optical processors and performance modelling. Networking with professionals in the industry can provide valuable insights and potentially lead to referrals for the position.
✨Tip Number 3
Prepare to discuss specific projects where you've built performance models or simulators. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will showcase your problem-solving skills.
✨Tip Number 4
Brush up on your C++ and Python skills, especially in the context of developing simulators. Consider working on a small project or contributing to open-source initiatives that involve these languages to strengthen your practical experience.
We think you need these skills to ace Modelling Engineer (Mid-Staff)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in performance modelling, particularly with CPUs, GPUs, and custom accelerators. Emphasise your proficiency in C++ and Python, as well as any experience with discrete-event or cycle-accurate simulators.
Craft a Compelling Cover Letter: In your cover letter, express your passion for optical computing and AI. Discuss specific projects or experiences that demonstrate your ability to lead critical projects and collaborate cross-functionally, as mentioned in the job description.
Showcase Relevant Skills: Highlight your understanding of computer architecture fundamentals and familiarity with machine learning frameworks like PyTorch or TensorFlow. Provide examples of how you've used these skills in past roles to solve complex performance challenges.
Prepare for Technical Questions: Anticipate technical questions related to performance modelling and simulation. Be ready to discuss your experience with benchmarking, bottleneck analysis, and design-space exploration, as these are key responsibilities of the role.
How to prepare for a job interview at La Fosse Associates Limited
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with performance modelling, particularly in relation to CPUs, GPUs, and custom accelerators. Highlight specific projects where you've built simulators or models, and be ready to explain the methodologies you used.
✨Demonstrate Cross-Functional Collaboration
Since the role involves working closely with hardware, compiler, and ML framework teams, share examples of how you've successfully collaborated across different teams in previous roles. Emphasise your communication skills and ability to translate complex technical concepts.
✨Prepare for Technical Questions
Expect questions on computer architecture fundamentals, such as memory systems and queuing theory. Brush up on Amdahl's and Gustafson's laws, and be ready to discuss how these concepts apply to performance modelling in optical compute systems.
✨Highlight Your Problem-Solving Skills
The role requires solving complex performance challenges, so prepare to discuss specific instances where you've identified bottlenecks and optimised performance. Use data-driven examples to illustrate your analytical approach and the impact of your solutions.
