Software Engineering Manager, AI Networking Menlo Park, CA • AI Infrastructure +1 more • Artifi[...]

Meta; Menlo Park (CA); On-site; USD 177,000 - 251,000; Full time

Job summary

Join an innovative team at a forward-thinking company where you'll lead the development of cutting-edge AI networking software. This role focuses on enhancing the performance and reliability of distributed AI communication stacks, crucial for large-scale ML products. You will collaborate with cross-functional teams and external partners, shaping the technical roadmap while mentoring engineers to excel in their careers. This is a unique opportunity to work on groundbreaking technologies that influence the future of AI and networking, making a significant impact in a dynamic environment.

Benefits

Equity

Bonus

Comprehensive Benefits

Qualifications

• 2+ years of experience managing a networking related Software Engineering Team.
• Working knowledge of network transport stack such as RoCE (RDMA).

Responsibilities

• Define technical roadmap and drive execution for the team.
• Guide team members in skill development and address underperformance.

Skills

Team Management

Networking Knowledge

Software Development

Cross-Functional Communication

Performance Tuning

Education

BS in Computer Science

MS in Computer Science

Tools

PyTorch

Caffe2

TensorFlow

NCCL

Job description

Software Engineering Manager, AI Networking

In this role, you will be a member of the Network AI Software team and part of the bigger DC networking organization. The team develops and owns the software stack around collective communication libraries around Meta. At a high level, the team aims to enable Meta-wide ML products and innovations to leverage our large-scale training and inference fleet through an observable, reliable and high-performance distributed AI communication stack. Currently, one of the team’s focus is on building customized features, SW benchmarks, performance tuners and SW stacks around PyTorch to improve the full-stack distributed ML reliability and performance (e.g. Large-Scale GenAI/LLM training) from the trainer down to the network communication layer. We are seeking leaders to work on the space of GenAI/LLM scaling reliability and performance.

Responsibilities

1. Help define technical roadmap for the team, drive execution of associated tasks and support the team in resolving dependencies.
2. Collaborate effectively with other groups such as Hardware, Infrastructure, Operations.
3. Interact with external partners as needed in resolving dependencies associated with objectives.
4. Guide and help team members develop appropriate skillsets to grow in their careers, and where necessary address underperformance.
5. Communicate cross-functionally and drive engineering efforts.

Minimum Qualifications

1. BS or MS in Computer Science or related technical discipline or equivalent experience.
2. 2+ years of experience managing a networking related Software Engineering Team.
3. Working knowledge of network transport stack such as RoCE (RDMA).
4. Experience with software development for Distributed and Embedded systems.
5. Experience recruiting and managing Software Engineers.

Preferred Qualifications

1. Experience with NCCL and distributed GPU reliability/performance improvement on RoCE/Infiniband.
2. Experience working with Deep Learning frameworks like PyTorch, Caffe2 or TensorFlow.
3. Knowledge of ML, deep learning and LLM.

Compensation: $177,000/year to $251,000/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.

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.