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# Software Engineer, Systems ML - Compilers

- **Company:** The Meta Game, Inc.
- **Location:** Austin, TX, United States
- **Experience:** Experienced
- **Salary:** $183,997.0 - $257,000.0
- **Contract:** Permanent contract
- **Skills:** Computer-Aided Design, Artificial Intelligence, Computer Vision, Augmented Reality, C++ (Programming Language), Compilers, Code Generation, Program Optimization, Computer Engineering, Software Design Patterns, Firmware, Machine Learning, Performance Tuning, Tensorflow, Software Engineering, Toolchain, Graphics Processing Unit (GPU), Application Specific Integrated Circuits, Pytorch, Virtual Reality, Deep Learning, Information Technology, TensorRT, Hardware Infrastructure, Mixed Reality
- **Published:** September 27, 2026
- **Apply:** https://dejobs.org/x/x/B86CD908D326433886C90A59A60A911A/job/

## About the Role

9. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
 10. 3+ years of experience in developing compilers, toolchains, or code optimization software
 11. Experience with LLVM, MLIR, or similar compiler infrastructure frameworks
 12. Experience in designing intermediate representations and implementing compiler optimization passes
 13. Experience with hardware architectures such as GPUs, TPUs, or custom AI accelerators
 14. Experience in software development using C++ for compiler and systems-level programming
 15. Experience leading end-to-end technical design and delivery of compiler infrastructure initiatives across multiple teams

Preferred Qualifications:

Preferred Qualifications:

 16. Experience developing in ML frameworks such as PyTorch or TensorFlow at the system level
 17. Experience co-designing software and hardware features with silicon architecture teams
 18. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
 19. Experience with ExecuTorch, TensorRT, XLA, or similar ML compilation and deployment frameworks
 20. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
 21. Experience with power and performance optimization for resource-constrained edge devices
 22. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
 23. Experience with machine-code generation or compiler back-ends targeting edge or on-device inference workloads

## Description

Reality Labs (RL) focuses on delivering Meta's vision through Virtual Reality (VR), Augmented Reality (AR) and Wearable AI Devices. The compute performance and power efficiency requirements of our AI devices require custom silicon. Reality Labs Silicon team is driving the state of the art forward with breakthrough work in computer vision, machine learning, mixed reality, graphics, displays, sensors, and new ways to map the human body. Our chips will unlock personalized on-device AI capabilities and blend virtual, physical worlds on wearable devices. We believe the only way to achieve our goals is to look at the entire stack, from transistors, through architecture, firmware, and algorithms.We are seeking a software engineer to support the development of the compiler tool-chain for state-of-the-art deep learning hardware components optimized for AR/VR systems. You will be part of our efforts to architect, design and implement a clean slate compiler for this activity and will be part of a
team that includes compiler, machine learning algorithms and software, firmware and ASIC experts. You will contribute to a full stack development effort compiling PyTorch models down to binaries for custom hardware accelerator blocks., 1. Lead the architecture and implementation of ML compiler infrastructure, including intermediate representations (IR), optimization passes, and code generation targeting custom AI accelerators

 2. Design and implement compiler transformations informed by hardware architecture constraints for GPU, TPU, and edge AI accelerators
 3. Drive the development of LLVM/MLIR-based toolchains for compiling PyTorch models to optimized binaries for custom silicon
 4. Work with hardware architects to co-design compiler features that maximize performance, power efficiency, and programmability for edge devices
 5. Analyze and improve the efficiency, scalability, and stability of compiler toolchains, ensuring they can be extended to new hardware targets
 6. Lead technical roadmapping for compiler infrastructure initiatives, coordinate execution across teams, and mentor engineers on compiler design patterns
 7. Conduct design and code reviews, evaluate code performance, and drive resolution of compiler and cross-disciplinary system issues
 8. Interface with other compiler-focused teams (PyTorch, ExecuTorch) to evaluate and incorporate innovations


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