Software Engineer, SystemML - AI Networking

Onsite$154,003 - $217,000/yrPosted 2 weeks ago

We tailor your resume to this role and apply for you in seconds.

Apply to Software Engineer, SystemML - AI Networking at Meta

Job details

Location: Menlo Park, California
Work type: Onsite
Compensation: $154,003 - $217,000/yr
Posted: 2 weeks ago
Apply on: metacareers.com

About this role

In this role, you will be a member of the AI Networking Software team and part of the bigger DC networking organization. The team develops and owns the software stack around NCCL (NVIDIA Collective Communications Library), which enables multi-GPU and multi-node data communication through HPC-style collectives. NCCL has been integrated into PyTorch and is on the critical path of multi-GPU distributed training. In other words, nearly every distributed GPU-based ML workload in Meta Production goes through the software stack the team owns. At the high level, the team aims to enable Meta-wide ML products and innovations to leverage our large-scale GPU training and inference fleet through an observable, reliable and high-performance distributed AI/GPU communication stack. Currently, one of the team’s focus is on building customized features, software benchmarks, performance tuners and software stacks around NCCL and PyTorch to improve the full-stack distributed ML reliability and performance (e.g. Large-Scale GenAI/LLM training) from the trainer down to the inter-GPU and network communication layer. And we are seeking engineers to work on the space of GenAI/LLM scaling reliability and performance.

Responsibilities

Providing technical leadership for the collective communication library development on Meta's large-scale GPU training infra with a focus on GenAI/LLM scaling

Minimum Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Proven C/C++ and Python programming skills
Proven track record of leading successful projects
Experience leading cross-functional technical projects and communicating technical decisions to both technical and non-technical stakeholders
Specialized experience in one or more of the following machine learning/deep learning domains: Distributed ML Training, GPU architecture, ML systems, AI infrastructure, high performance computing, performance optimizations, or Machine Learning frameworks (e.g. PyTorch)

Preferred Qualifications

Experience with NCCL and distributed GPU performance analysis on RoCE/Infiniband
Knowledge of GPU architectures and CUDA programming
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Experience working with DL frameworks like PyTorch, Caffe2 or TensorFlow
Experience in AI framework and trainer development on accelerating large-scale distributed deep learning models
Experience with both data parallel and model parallel training, such as Distributed Data Parallel, Fully Sharded Data Parallel (FSDP), Tensor Parallel, and Pipeline Parallel
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
PhD in Computer Science, Computer Engineering, or relevant technical field
Knowledge of ML, deep learning and LLM
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Experience in HPC and parallel computing

Compensation

$154,003/year - $217,000/year; Country: US; Bonus eligible; Equity eligible

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.

California Notice

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

Equal Opportunity

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.

Accommodations

Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form.

Ready to apply to Meta?

We tailor your resume to this role and apply for you.