{"schemaVersion":"jobsearcher.job.v1","id":"9816519e1b615019da044044","url":"https://jobsearcher.com/jobs/9816519e1b615019da044044","canonicalUrl":"https://jobsearcher.com/jobs/9816519e1b615019da044044","title":"Software Engineer, Systems Machine Learning","description":"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.\n\nSoftware Engineer, Systems Machine Learning Responsibilities:\n\nDesign and develop software tools across the MTIA tooling ecosystem, including debugging, profiling, performance analysis, memory analysis, and monitoring infrastructure\nOwn features and components end-to-end, from design through implementation, testing, and deployment\nBuild and improve tooling infrastructure that enables engineers to efficiently develop, test, and optimize AI workloads on MTIA hardware\nCollaborate with the MTIA compiler, runtime, kernel, and hardware teams to integrate tooling hooks and support new platform capabilities\nProactively identify gaps in the tooling ecosystem and propose solutions to improve developer productivity\nContribute to technical design discussions, write design documents for medium-scope projects, and participate in code reviews\nPartner with internal product teams across advertising, recommendations, and generative AI to understand developer pain points and improve tool usability\n\nMinimum Qualifications:\n\nCurrently 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 Meta\nBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience\nBachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience\n2+ years of experience in software engineering, with exposure to systems software, developer tooling, or infrastructure\nProficiency in C++ and Python, including systems-level programming concepts\nExperience working across multiple layers of a system stack (e.g., application, runtime, OS/driver, or hardware interfaces)\nTrack record of independently delivering software projects from design through production deployment\nExperience debugging and resolving issues in complex software systems (e.g., using log analysis, stack traces, or system-level diagnostic tools)\n\nPreferred Qualifications:\n\nExposure to accelerator ecosystems (GPU/CUDA, TPU, custom ASICs) or heterogeneous computing environments\nDemonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies\nExperience building developer tools such as debuggers, profilers, build systems, CLI tools, monitoring dashboards, or diagnostic utilities\nContributions to open-source projects demonstrating tooling or system software interest\nExperience in using data-driven methods to evaluate tooling effectiveness and to prioritize improvements\nFamiliarity with Linux debugging and profiling tools (gdb, perf, strace, eBPF, valgrind) or similar diagnostic infrastructure\nExperience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)\nFamiliarity with ML frameworks (PyTorch, TensorFlow) or compiler infrastructure (LLVM, MLIR, TVM)\nExperience with distributed systems debugging, profiling, or monitoring at scale\nDemonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)\n\nAbout Meta:\n\nMeta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.\n\nMeta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.\n\nMeta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.\n\n$121,992/year to $181,000/year + bonus + equity + benefits\n\nIndividual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.","company":"Meta","rawCompany":"meta","city":"Austin","state":"TX","isRemote":false,"isActive":true,"createdAt":"2026-10-24T09:04:51.332Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1211.00","title":"Computer Systems Analysts","slug":"computer-systems-analysts"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Software Engineer, Systems Machine Learning","description":"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.\n\nSoftware Engineer, Systems Machine Learning Responsibilities:\n\nDesign and develop software tools across the MTIA tooling ecosystem, including debugging, profiling, performance analysis, memory analysis, and monitoring infrastructure\nOwn features and components end-to-end, from design through implementation, testing, and deployment\nBuild and improve tooling infrastructure that enables engineers to efficiently develop, test, and optimize AI workloads on MTIA hardware\nCollaborate with the MTIA compiler, runtime, kernel, and hardware teams to integrate tooling hooks and support new platform capabilities\nProactively identify gaps in the tooling ecosystem and propose solutions to improve developer productivity\nContribute to technical design discussions, write design documents for medium-scope projects, and participate in code reviews\nPartner with internal product teams across advertising, recommendations, and generative AI to understand developer pain points and improve tool usability\n\nMinimum Qualifications:\n\nCurrently 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 Meta\nBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience\nBachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience\n2+ years of experience in software engineering, with exposure to systems software, developer tooling, or infrastructure\nProficiency in C++ and Python, including systems-level programming concepts\nExperience working across multiple layers of a system stack (e.g., application, runtime, OS/driver, or hardware interfaces)\nTrack record of independently delivering software projects from design through production deployment\nExperience debugging and resolving issues in complex software systems (e.g., using log analysis, stack traces, or system-level diagnostic tools)\n\nPreferred Qualifications:\n\nExposure to accelerator ecosystems (GPU/CUDA, TPU, custom ASICs) or heterogeneous computing environments\nDemonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies\nExperience building developer tools such as debuggers, profilers, build systems, CLI tools, monitoring dashboards, or diagnostic utilities\nContributions to open-source projects demonstrating tooling or system software interest\nExperience in using data-driven methods to evaluate tooling effectiveness and to prioritize improvements\nFamiliarity with Linux debugging and profiling tools (gdb, perf, strace, eBPF, valgrind) or similar diagnostic infrastructure\nExperience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)\nFamiliarity with ML frameworks (PyTorch, TensorFlow) or compiler infrastructure (LLVM, MLIR, TVM)\nExperience with distributed systems debugging, profiling, or monitoring at scale\nDemonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)\n\nAbout Meta:\n\nMeta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.\n\nMeta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.\n\nMeta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.\n\n$121,992/year to $181,000/year + bonus + equity + benefits\n\nIndividual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.","datePosted":"2026-10-24T09:04:51.332Z","dateModified":"2026-10-24T09:04:51.332Z","hiringOrganization":{"@type":"Organization","name":"Meta","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Austin","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"9816519e1b615019da044044"},"url":"https://jobsearcher.com/jobs/9816519e1b615019da044044"}}