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# ASIC Engineer, Performance Architecture...

- **Company:** The Meta Game, Inc.
- **Location:** Pierre, SD, United States
- **Experience:** Expert
- **Salary:** $178,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Assembly Language, C++ (Programming Language), Computer Engineering, Data Centers, Digital Technology, Firmware, Hardware Description Language, Python (Programming Language), Machine Learning, Regression Testing, SystemC, SystemVerilog, VHSIC Hardware Description Language (VHDL), Multithreading, Graphics Processing Unit (GPU), High Performance Computing, Performance Testing, Application Specific Integrated Circuits, Information Technology, Low Latency, Physical Design
- **Published:** August 28, 2026
- **Apply:** https://www.juju.com/job/00000000gpc2dv

## About the Role

ASIC Engineer, Performance Architecture and Modeling Responsibilities:

 1. Define and own the performance modeling strategy for custom infrastructure ASICs, including development of cycle-accurate and transaction-level simulation environments, 12. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

 13. 8+ years of experience in ASIC design, silicon engineering, or a related technical field

 14. 5+ years of experience in ASIC performance modeling, microarchitectural analysis, or pre-silicon simulation for custom silicon or SoC designs

 15. Proficiency in C++ and Python for developing simulation models, automation frameworks, and performance analysis tools

 16. Experience developing cycle-accurate or transaction-level performance models using C++ and SystemC for complex digital systems including processors, memory subsystems, or high-speed interconnects

 17. Experience with performance analysis of data center, AI accelerator, or high-performance computing workloads on custom silicon

 18. Experience defining microarchitectural specifications and driving cross-functional alignment across architecture, RTL, and physical design teams

 19. Experience with assembly programming languages, and compiler technologies

Preferred Qualifications:

Preferred Qualifications:

 20. Experience with hardware description languages (e.g., SystemVerilog, VHDL) and simulation environments used in ASIC development flows

 21. Experience building or scaling performance modeling infrastructure for hyperscale data center ASICs, including network, storage, or AI inference accelerator designs

 22. Familiarity with post-silicon performance validation and model-to-hardware correlation methodologies

 23. Experience developing Python-based automation pipelines for simulation orchestration, regression testing, and performance data analysis

 24. Experience with GPU, machine learning, multi-threaded programming paradigm

 25. Experience with high-level synthesis, power-performance-area trade-off analysis, or PPA-driven microarchitectural optimization

## Description

Meta's Silicon Engineering organization is building custom silicon solutions that power the infrastructure underpinning Meta's AI and data center workloads at scale. As an ASIC Engineer specializing in performance and modeling, you will define and drive the architectural performance analysis, pre-silicon modeling, and microarchitectural exploration of custom ASICs designed for Meta's infrastructure. In this role, you will establish the performance modeling methodology and long-term silicon roadmap strategy, partnering with architecture, design, and software teams to ensure Meta's infrastructure silicon meets the demanding throughput, latency, and efficiency targets required at hyperscale., 3. Develop and validate pre-silicon performance models that accurately predict post-silicon behavior for data center workloads

 4. Develop low-level workloads and kernels for machine learning training and inference applications

 5. Establish performance analysis methodologies, benchmarking frameworks, and bottleneck identification techniques across the full ASIC pipeline

 6. Collaborate with architecture, RTL design, and physical design teams to translate performance requirements into implementable microarchitectural specifications

 7. Partner with software and systems teams to co-optimize workload scheduling, firmware, and driver behavior against silicon performance characteristics

 8. Lead cross-functional technical reviews and communicate performance modeling results and architectural recommendations to engineering leadership

 9. Define long-term performance modeling infrastructure roadmaps, including tooling, automation, and simulation platform investments

 10. Mentor other engineers on performance modeling techniques, simulation methodology, and microarchitectural analysis best practices

 11. Identify and resolve performance gaps between modeled and measured silicon behavior through structured root-cause analysis and model calibration


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