Software Engineer - Machine Learning Systems

Meta — United States · Posted ~3 hours ago

Mid Full-time

Skills

C++ Python Machine learning infrastructure Distributed systems ML training pipelines Inference systems Performance optimization Machine Learning Distributed Computing

🔓 Log in to save this job, tailor your resume & track your apply process — 7 days free, no card needed.

Log in to add to target list

Summary ✨ AI‑Generated

A software engineering position focused on building and optimizing large-scale machine learning systems, including training pipelines, inference infrastructure, and performance-critical components.

Highlights

Work on large-scale machine learning infrastructure and high-performance systems with opportunities to collaborate across engineering and research teams.

Description

Meta is seeking a Software Engineer to join our Systems ML Engineering team, focused on building and optimizing the machine learning infrastructure that powers Meta's products at massive scale. In this role, you will design and develop high-performance ML systems, working across the full stack from model training and inference pipelines to hardware-aware optimizations. You will collaborate with researchers, platform engineers, and product teams to accelerate ML workloads and improve the efficiency of AI infrastructure that serves billions of users. Software Engineer, Systems ML Responsibilities: Design, build, and optimize large-scale ML training and inference systems, including distributed computing frameworks and hardware-accelerated pipelinesDevelop and maintain high-performance ML infrastructure components in C++ and Python, ensuring reliability, scalability, and low-latency executionIdentify and resolve performance bottlenecks across the ML stack using profiling, instrumentation, and benchmarking toolsArchitect and evaluate trade-offs in ML system design, including memory bandwidth, compute utilization, and I/O throughputPartner with research and product teams to translate ML model requirements into efficient infrastructure solutionsWrite automated tests covering expected behaviors, failure modes, and error paths for ML infrastructure components, and build monitoring and alerting for production anomaliesContribute to staged rollout strategies using feature flagging and experimentation frameworks to safely deploy ML system changesProduce accurate technical documentation when introducing new ML infrastructure features or updating existing systemsParticipate in on-call rotations to investigate and mitigate production incidents affecting ML serving systems, and contribute detailed retrospectivesProvide constructive code review feedback to other engineers and contribute to engineering programs that improve the health and quality of the ML infrastructure codebase Minimum Qualifications: 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 Meta2+ years of experience in software engineering with a focus on machine learning systems, AI infrastructure, or high-performance computingExperience developing or optimizing ML training or inference pipelines using frameworks such as PyTorch, TensorFlow, or equivalentExperience with distributed computing architectures and large-scale systems design for ML workloadsExperience programming in C++ and Python for performance-critical systemsExperience using profiling and performance analysis tools to identify and resolve bottlenecks in ML or compute-intensive systems Preferred Qualifications: 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)Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologiesDemonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)Experience with ML compiler technologies such as MLIR, LLVM, TVM, XLA, or IREEExperience with GPU programming using CUDA, ROCm, or equivalent hardware accelerator kernel developmentExperience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologiesExperience optimizing large-scale ranking or recommendation model inference on AI accelerator hardware such as GPUs or TPUsExperience with hardware-software co-design, including numerics optimization and SIMD or vectorization techniques About Meta: Meta 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. Meta 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. Meta 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. $121,992/year to $181,000/year + bonus + equity + benefits Individual 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.