软件工程经理，AI内核与性能优化 — MTIA软件

Meta（Meta Platforms）岗位：Software Engineering Manager, AI Kernels & Performance Optimization — MTIA Software Responsibilities

Lead and manage a team of systems engineers delivering on multiple concurrent projects across ambiguous, high-impact areas of Meta's platform infrastructure

Drive roadmap creation and technical strategy for systems-level software, ensuring alignment with broader product and engineering goals

Contribute directly to technical work including architecture reviews, design documents, and hands-on coding to maintain credibility and unblock the team

Identify and resolve systemic issues affecting team velocity, including on-call load, technical debt, and gaps in tooling or automation

Partner with product, design, and data science to ensure engineers contribute across disciplines and deliver outcomes that move business metrics forward

Set clear goals and expectations for individual engineers, provide timely and actionable feedback, and proactively address performance gaps

Manage staged rollouts and feature delivery using feature flagging and A/B testing frameworks, ensuring high engineering quality and system reliability

Recruit, onboard, and develop engineers, building a team structure that minimizes single points of failure and scales with organizational needs

Communicate team goals, technical decisions, and progress clearly to cross-functional partners and leadership, including written design proposals and postmortems

Participate in org-wide engineering contributions, sharing effective workflows, tooling practices, and systems engineering patterns across the broader organization

4+ years of experience in software engineering with a focus on systems-level software, platform infrastructure, or distributed systems

2+ years of experience managing or leading engineering teams, including setting technical direction and supporting engineer growth

Experience driving technical roadmaps and executing against them with measurable outcomes in ambiguous or high-complexity environments

Experience identifying and resolving engineering efficiency issues such as on-call burden, technical debt, or gaps in automation

Experience collaborating across product, design, and data functions to deliver software that achieves business and user impact

Track record of hands-on technical contribution as a manager, including authoring design documents, reviewing system architectures, or writing production code

Experience with hardware/software co-design cycles: collaborating with silicon architects, validating architectural features with real kernels, and influencing hardware roadmaps based on software performance analysis

Experience working on customized AI accelerators (TPU, AI ASICs, or similar non-GPU architectures) with direct involvement in kernel development and roofline enablement

Familiarity with transformer and attention kernel design: FlashAttention-class algorithms, KV-cache management, paged and chunked attention, MoE routing and expert dispatch

Experience with distributed execution and collective communication (NCCL/RCCL-class primitives, tensor and expert parallelism, overlapping communication with compute)

Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Experience managing or leading teams working on high-performance kernel development, accelerator software, HPC, or ML systems performance

Hands-on experience with kernel development for novel hardware — including pre-silicon bring-up on simulators/emulators and first-light optimization on new silicon

Experience building or contributing to high-performance kernel libraries or frameworks — CUTLASS, cuBLAS, cuDNN, Triton, Helion, oneDNN, Composable Kernel, or comparable internal equivalents

Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

Experience with compiler and codegen technologies relevant to kernels: MLIR, LLVM, TVM, XLA, Halide, or polyhedral scheduling

Experience with low-precision numerics and quantization — FP8/E4M3/E5M2, MX and other block-scaled formats, INT8/INT4 — including error analysis and calibration

Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

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.

For those who live in or expect to work from California if hired for this position, please click here for additional information.

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.

Meta is proud to be an Equal Employment Opportunity employer.

We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.

You may view our Equal Employment Opportunity notice here.

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4+ years of experience in software engineering with a focus on systems-level software, platform infrastructure, or distributed systems.

2+ years of experience managing or leading engineering teams, including setting technical direction and supporting engineer growth.