Architecture Modeling Engineer

About This Opportunity

We are representing a confidential semiconductor organization developing next-generation AI acceleration technology. Our talent team is searching for an Architecture Modeling Engineer to join their Paris offices and play a critical role in performance modeling and workload optimization for cutting-edge hardware.

This is a high-impact position where you'll bridge hardware architecture and software performance, turning complex workload requirements into actionable design decisions and optimized execution on novel silicon.

Responsibilities

• Develop fast, flexible performance models to evaluate AI accelerator architecture choices and guide early design decisions
• Work closely with software teams to characterize key AI workloads, kernels, dataflows, and system bottlenecks
• Collaborate with hardware architects to model compute, memory, interconnect, and scheduling behavior across proposed architectures
• Drive rapid performance studies and trade-off analyses across throughput, latency, utilization, bandwidth, and efficiency
• Help define and validate the programming model and workload mapping strategy for the accelerator
• Following architecture definition, optimize compute kernels and key workloads for the target hardware hands-on with the software team
• Build lightweight simulation, profiling, and analysis tools that support fast iteration from architecture exploration through software optimization

What We're Looking For

Required:

• Strong mathematical background, particularly in linear algebra, probability, numerical methods, and quantitative performance analysis
• Strong knowledge of computer architecture, including compute pipelines, memory hierarchies, interconnects, and parallel execution
• Strong C/C++ and Python programming skills
• Experience analyzing and optimizing performance-critical kernels or low-level compute workloads
• Good understanding of AI/ML workloads, tensor operations, data movement, and common execution patterns
• Ability to work across hardware and software teams and translate workload behavior into architecture and software requirements
• Proficient English language skills

Nice to Have:

• Strong industry knowledge about AI hardware, GPUs, memory generations, rack-scale computing
• Experience building performance models, simulators, or analytical models for CPUs, GPUs, NPUs, or other accelerators
• Experience with profiling, benchmarking, and identifying hardware or software performance bottlenecks
• Experience in novel computing architectures: analog computing, in-memory computing, heterogeneous systems

How We Work With You

Candidates apply directly through Get A Job.ai. Our recruiting team will conduct an initial screening to understand your background and fit for this role. If there's a strong match, we will submit your profile to our client for consideration. Please do not attempt to contact the client directly, as all communication is managed through our talent team to ensure a smooth and professional process.

Pay

Compensation details will be discussed during the screening process and are competitive based on location, experience, and market rates for similar positions.

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