Senior Performance Modelling Engineer at Flux

San Francisco, California, United States

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$230,000 – $282,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Optical Computing, Hardware, Machine LearningIndustries

Requirements

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

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

Key technologies and capabilities for this role

Performance ModellingFunctional SimulatorCycle-Accurate ModelsPythonC++Workload AnalysisLLMsDiffusion ModelsGraph WorkloadsTrace ParsingStatistical AnalysisVisualizationCI IntegrationRTLHardware ArchitectureCompilerML Frameworks

Questions & Answers

Common questions about this position

What is the salary range for the Senior Performance Modelling Engineer role?

The starting salary is $230,000 - $282,000 depending on experience.

Is this position remote or onsite?

This is an onsite position in San Francisco.

What skills and experience are required for this role?

Candidates need 5+ years building performance or power models for CPUs, GPUs, ASICs, or accelerators, strong coding in C++ and Python with simulator experience, solid computer-architecture fundamentals, familiarity with ML workloads and frameworks, and excellent data-visualization skills.

What benefits are offered for this position?

The role offers generous stock options in a rapidly growing AI company.

What makes a strong candidate for this role?

A strong candidate has a Bachelor’s+ in EE, CS, Physics, Applied Maths or related, plus personal or open-source projects in simulators, ML kernels, or performance analysis.

Flux

AI-powered platform for PCB design

About Flux

Flux.ai provides a platform for designing and building printed circuit boards (PCBs) within the electronic design automation (EDA) market. The platform features an AI-powered assistant named Copilot, which helps users streamline the PCB design process, making it more efficient. Users can sign up for free and access basic features, with the option to upgrade to premium subscription plans for additional services. This freemium model allows engineers, designers, and electronics enthusiasts to engage with the platform at their own pace. Flux.ai differentiates itself from competitors by integrating AI assistance directly into the design workflow, enhancing user experience and accessibility in PCB design.

San Francisco, CaliforniaHeadquarters

2019Year Founded

$11.7MTotal Funding

EARLY_VCCompany Stage

Hardware, Consumer Software, AI & Machine LearningIndustries

51-200Employees

Benefits

Remote Work Options

Risks

Over-reliance on AI designs may lead to quality control issues and vulnerabilities.

New features like Smart Vias may increase complexity, potentially confusing users.

Intense competition from GenAI tools like SnapMagic could divert users from Flux.

Differentiation

Flux offers the first AI-powered hardware design assistant integrated into a PCB tool.

Flux's Copilot provides personalized design recommendations, enhancing user experience and efficiency.

Smart Vias technology simplifies high-density PCB designs, setting Flux apart from competitors.

Upsides

Increased adoption of AI tools boosts demand for Flux's innovative design platform.

Remote work trends align with Flux's cloud-based SaaS model, enhancing collaboration.

Generative AI advancements create opportunities for Flux to lead in hardware design.

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