Software Engineer, Simulation

Meta; Bellevue (WA); On-site; USD 180,000 - 240,000; Full time

Job summary

Meta is seeking an experienced software engineer to join the MTIA team to build simulators and other early software development platforms for pre-silicon AI accelerator work. You will own simulation models and contribute to scalable infrastructure.

Collaborate across hardware and software domains to evaluate data center performance, optimize inference and training workloads, and ensure reliable, high-performance accelerator designs.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience
• Master's or PhD in Computer Science, Computer Engineering, or related field
• 5+ years of experience in developing C++ codebase
• 5+ years experience in developing Python codebase
• Experience with performance benchmarking on distributed at-scale model training/inference; familiarity with SystemC, Qemu, Virtual Platform
• Demonstrated AI skill development and ability to integrate AI tools to optimize workflows
• Experience with responsible, ethical AI practices and bias mitigation
• Experience in AI/ML infrastructure/HPC domains with hardware accelerators/interconnects

Responsibilities

• Contribute to developer infrastructure, including simulation and HW emulation platforms for Meta's accelerator programs
• Support networking and compute hardware acceleration techniques to improve ML inference and training model performance
• Implement simulation models for Meta's Accelerator ASICs and evaluate data center performance
• Perform architectural analysis to ensure performance, scalability, and reliability
• Collaborate with architects and engineers to integrate simulation results into system design
• Define firmware for accelerators using instruction set simulators
• Collaborate with hardware teams to ensure accurate modeling of accelerator functionalities

Skills

C++

Python

SystemC

Qemu

Virtual Platform

AI tooling integration

Distributed training

NCCL

CUDA

Performance benchmarking

Education

Bachelor's degree

Master's or PhD

Tools

NCCL

PyTorch

CUDA

Job description

About

We are seeking an experienced software engineer to join the MTIA (Meta Training and Inference Accelerator) software team, to work on simulators and other early software development platforms. The simulators you build will be critical for pre-silicon development, allowing the whole team to develop software before hardware is available. This is an opportunity to work with a dedicated engineering team, collaborating with a large set of cross-functional partners. The program carries top-level executive visibility as a key AI infrastructure initiative, and the team values deep technical contributions with extensive knowledge-sharing.

Responsibilities

• Contribute to our developer infrastructure, including simulation and HW emulation platforms, to enable performance measurement and optimization for Meta's in-house accelerator programs
• Support networking and compute hardware acceleration techniques to improve ML inference and training model performance
• Implement simulation models for Meta's Accelerator ASICs, develop and analyze various scenarios to evaluate data center performance and identify potential improvements
• Perform an architectural analysis to ensure that system designs meet performance, scalability, and reliability requirements
• Collaborate with architects and engineers to integrate simulation results into system design processes
• Use instruction set simulators to define performant firmware for Meta's training/inference accelerators
• Collaborate with hardware teams to ensure accurate modeling and simulation of accelerator functionalities

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Masters or PhD in Computer Science, Computer Engineering, or any other relevant technical field
• 5+ years of experience in developing C++ codebase
• 5+ years experience in developing Python codebase
• Understanding of performance and benchmarking measurement and optimization on collective communications and distributed at-scale model training and inference Experience with SystemC, Qemu, Virtual Platform
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience in one or more of the following machine learning/deep learning domains: hardware accelerators, AI Infrastructure, and/or high performance computing (HPC), particularly pertaining to interconnect and collective
• Full-stack experience and understanding of AI/HPC systems, from HW/infrastructure through the application layer, performance optimizations, including familiarity with relevant tools, libraries, and frameworks (e.g., NCCL, PyTorch, CUDA)