
Software Engineering Manager, MTIA
Required skills
- LLVM compiler infrastructure
- early software development platforms
- simulators
- AI workloads
- custom accelerators
- ISA design
- hardware/software co-design
- pre-silicon development
- code reviews
- testing practices
Nice to have
- responsible, ethical AI practices
- risk assessment
- bias mitigation
- quality and accuracy reviews
- PyTorch
- TensorFlow
Role summary
Meta is seeking a Software Engineering Manager for its MTIA Software team to lead the development of LLVM compiler infrastructure and early software development platforms, including simulators. This role is critical for accelerating AI workloads on custom accelerators and enabling pre-silicon development. The manager will drive technical direction, build and mentor engineers, and collaborate with hardware, frameworks, and model teams. The position requires at least 5 years of software team management experience and experience managing other managers, with a focus on full product life cycles. Preferred qualifications include experience with AI ethics, ML frameworks, specific simulator technologies, and hardware-software co-design.
Responsibilities
- You will drive the development of the LLVM compiler toolchain and early software development platforms, including cycle-accurate and functional simulators. You will lead teams of engineers and technical leaders delivering large-scale projects across compiler infrastructure and simulator development
- You will stay technically engaged, contributing hands-on through AI tools to evaluate the technical direction and quality across your teams. You will form trusted cross-functional partnerships with hardware, frameworks, and model teams while actively shaping strategy and roadmap. You will build and mentor engineers into AI-era leaders while maintaining engineering quality through code reviews, testing practices, and documentation
Minimum Qualifications
- At least 5 years of experience in managing a software team
- Demonstrated experience in managing other managers
- Proven understanding and experience in executing full product life-cycles (prototyping, deployment, and support)
Preferred Qualifications
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Knowledge of ML frameworks like PyTorch, TensorFlow, ONNX, MXNet, etc
- Cycle-accurate and functional simulators. RISC-V architecture and custom ISA tooling
- Triton and domain-specific languages. Experience working closely with hardware architectures such as Intel SIMD, GPU, RISC-V, AI accelerators etc
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Experience with different programming models for high-performance computations, e.g., GPU CUDA programming or OpenCL or OpenMP programming
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience in hardware-software development environments such as simulators, FPGA emulators, etc
- Experience in accelerating libraries on AI hardware, similar to cuBLAS, cuDNN, CUTLASS, HIP, ROCm etc
- LLVM compiler infrastructure and MLIR
$219,000/year to $301,000/year + bonus + equity + benefits
Sample Facebook interview questions
- 1
Design an AI data product
system designmedium - 2
Design a timer system
system designmedium - 3
Design Instagram
system designmedium - 4
Design Messenger
system designaverage - 5
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