Flux Computing · 1 month ago
Staff Performance Modelling Engineer
San Francisco, CA
Full-time
Onsite
Senior Level, Lead/Staff
7+ years expFlux Computing is seeking a Staff Performance Modelling Engineer to create and own analytical and simulation models that guide OTPU architecture and software evolution. The role involves building functional simulators and high-fidelity models of optical compute systems, while collaborating with engineering teams to ensure performance goals are met.
Artificial Intelligence (AI)HardwareMachine LearningManufacturingOptical Communication
No H1B
U.S. Citizen Only
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
Qualification
Required
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
Preferred
Advanced degree preferred but not required
Personal or open-source projects in simulators, ML kernels, or performance analysis are a significant plus
Benefits
Competitive salary and stock options
An extra ($24,000/year) incentive for those living within 20 minutes
Company
Flux Computing
Flux Computing designs optical AI accelerators that use light-based processors for training and inference on large models.
51-200 employees
Funding
Current Stage
Growth StageCompany data provided by crunchbase