Software Engineering Manager, Collective Communications at Meta
Menlo Park, CA 94025, USA -
Full Time


Start Date

Immediate

Expiry Date

16 Nov, 25

Salary

251000.0

Posted On

16 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Deep Learning, Performance Management, Rdma, Software Engineers, Computer Science, Machine Learning, Software Development, Embedded Systems, Mpi

Industry

Computer Software/Engineering

Description

NETWORK ENGINEERING

In this role, you will be a member of the Host Side Collective Communication Libraries (HCCL) software team and part of the Host Side Networking (HSN) organization within the DC Networking and Network Infra organizations. The team develops and owns the software stack around collective communication libraries for the internally developed Meta AI accelerator, Meta Training and Inference Accelerator (MTIA).At the high level, the team’s charter is to enable and performance optimize HCCL, our internally developed communication library for the MTIA. Currently, one of the team’s focus areas is standing up our first communications stack targeting various AI training workloads. The team is building the communications software stack including hardware customized features, software benchmarks and performance tooling.Specifically we are looking for people to lead designing, developing and operating some of the largest AI infrastructure in the world. This is a rare opportunity to work with the leading AI experts in the industry and build cutting edge AI communications infrastructure.

MINIMUM QUALIFICATIONS

  • 8+ years, or PhD + 4 years, of software engineering work experience, including hands on technical management
  • 2+ years of experience managing a networking related Software Engineering Team
  • BS or MS in Computer Science or related technical discipline or equivalent experience
  • Working knowledge of Collective Communications Libraries such as NVIDIA Collective Communications Library (NCCL) and Message Passing Interface (MPI)
  • Experience with software development for Distributed and Embedded systems
  • Demonstrated experience recruiting, building, structuring, and leading technical organizations, including performance management
  • Experience supporting, coaching, mentoring, and developing software engineers

PREFERRED QUALIFICATIONS

  • Experience with distributed GPU reliability/performance improvement on RoCE/Infiniband
  • Knowledge of network transport stack such as RoCE (RDMA)
  • Experience working with Deep Learning frameworks like PyTorch, Caffe2 or TensorFlow
  • Knowledge of Machine Learning, Deep Learning and Large Language Models
    For those who live in or expect to work from California if hired for this position.
Responsibilities
  • Help define technical roadmap for the team, drive execution of associated tasks and support the team in resolving dependencies
  • Guide and mentor team members to develop appropriate skillsets to grow in their careers, and where necessary address under performance
  • Collaborate effectively with other groups across the wider organisation such as Co-Design, Software, Hardware, Infrastructure and Operations teams
  • Communicate cross-functionally and drive engineering efforts
  • Interact with external partners as needed in resolving dependencies associated with objectives
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