Software Engineer, Systems Machine Learning

Meta; United States; A distancia; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

Meta is seeking a Software Engineer to join the MTIA Software Tooling team, building tooling for Meta's in-house AI accelerator. You will design, implement, and maintain developer tools to debug, profile, measure, and monitor AI workloads on MTIA hardware at scale, spanning CPUs, GPUs, and accelerator stacks.

You will collaborate across compiler, runtime, hardware, and ML framework domains to deliver a high-quality developer experience for Meta's custom AI accelerators.

Formación

• Bachelor's degree in CS/CE or equivalent completed before joining Meta.
• 2+ years of software engineering experience with systems software, tooling or infrastructure.
• Proficiency in C++ and Python with systems-level programming.
• Experience across multiple layers of a system stack (application, runtime, OS/driver, hardware).
• Track record delivering software from design to production deployment.
• Experience debugging complex software using logs, stack traces, or diagnostic tools.
• Exposure to accelerator ecosystems (GPU/CUDA, TPU, custom ASICs) or heterogeneous computing.
• Ongoing AI skill development and familiarity with emerging AI technologies.
• Experience building developer tools (debuggers, profilers, build systems, CLI tools, monitoring dashboards).
• Contributions to open-source projects demonstrating tooling or system software interest.
• Data-driven Methods to evaluate tooling effectiveness and improvements.
• Familiarity with Linux debugging and profiling tools (gdb, perf, strace, eBPF, valgrind).
• Familiarity with ML frameworks (PyTorch, TensorFlow) or compiler infrastructure (LLVM, MLIR, TVM).
• Experience with distributed systems debugging, profiling, or monitoring at scale.
• Ability to integrate AI tools to optimize workflows and drive impact.

Responsabilidades

• Design, build, and maintain developer tools to help engineers debug, profile, measure, and monitor AI workloads on MTIA hardware at scale.

Conocimientos

C++

Python

Systems software

Developer tooling

Infrastructure

Debugging complex software systems

AI tooling awareness

Open-source contributions

Data-driven tooling evaluation

Linux debugging tools

GPU/CUDA / accelerator ecosystems

ML frameworks familiarity

Distributed systems debugging

Cross-functional collaboration

Educación

Bachelor's degree in Computer Science or Computer Engineering or related field

Herramientas

Linux debugging tools (gdb, perf, strace, eBPF, valgrind)

LLVM

MLIR

TVM

PyTorch

TensorFlow

CUDA

Descripción del empleo

Meta is seeking a Software Engineer to join the MTIA (Meta Training & Inference Accelerator) Software Tooling team, which develops and maintains the tooling ecosystem for Meta's in-house AI accelerator ASICs. The Tooling team provides debugging, profiling, memory analysis, and monitoring capabilities for the whole MTIA Ecosystem, redefining ML accelerator tooling by leveraging Meta's full-stack ownership from silicon specs to fleet observability. In this role, you will design, build, and maintain developer tools that help engineers debug, profile, measure, and monitor AI workloads running on MTIA hardware at scale. You will work at the intersection of compilers, runtime, hardware, and ML frameworks, collaborating with cross-functional partners to deliver a high-quality developer experience for Meta's custom AI accelerators.

Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining MetaBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experienceBachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience2+ years of experience in software engineering, with exposure to systems software, developer tooling, or infrastructureProficiency in C++ and Python, including systems-level programming conceptsExperience working across multiple layers of a system stack (e.g., application, runtime, OS/driver, or hardware interfaces)Track record of independently delivering software projects from design through production deploymentExperience debugging and resolving issues in complex software systems (e.g., using log analysis, stack traces, or system-level diagnostic tools) Exposure to accelerator ecosystems (GPU/CUDA, TPU, custom ASICs) or heterogeneous computing environmentsDemonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologiesExperience building developer tools such as debuggers, profilers, build systems, CLI tools, monitoring dashboards, or diagnostic utilitiesContributions to open-source projects demonstrating tooling or system software interestExperience in using data-driven methods to evaluate tooling effectiveness and to prioritize improvementsFamiliarity with Linux debugging and profiling tools (gdb, perf, strace, eBPF, valgrind) or similar diagnostic infrastructureExperience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)Familiarity with ML frameworks (PyTorch, TensorFlow) or compiler infrastructure (LLVM, MLIR, TVM)Experience with distributed systems debugging, profiling, or monitoring at scaleDemonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)