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Benefits & Perks
•Equity
•Equity
Required Skills
Distributed Machine Learning
GPU Architecture
High Performance Computing
PyTorch
Performance Optimization
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 Py Torch 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 SW 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, SW benchmarks, performance tuners and SW stacks around NCCL and Py Torch 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 for engineers to work on the space of GenAI/LLM scaling reliability and performance.
Research Scientist, AI Networking (PhD) Responsibilities:
- Enabling reliable and highly scalable distributed ML training on Meta's large-scale GPU training infra with a focus on GenAI/LLM scaling
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 Meta
- Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
- Specialized experience in one or more of the following machine learning/deep learning domains: High speed networking (RDMA), Distributed ML Training, GPU architecture, ML systems, AI infrastructure, high performance computing, performance optimizations, or Machine Learning frameworks (e.g. Py Torch)
- Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment
Preferred Qualifications:
- Experience with NCCL/RCCL/OneCCL and distributed GPU reliability/performance improvement on RoCE/Infiniband
- Experience working with DL frameworks like Py Torch, Caffe2 or Tensor Flow
- Experience with both data parallel and model parallel training, such as Distributed Data Parallel, Fully Sharded Data Parallel (FSDP), Tensor Parallel, and Pipeline Parallel
- Experience in AI framework and trainer development on accelerating large-scale distributed deep learning models
- Experience in HPC and parallel computing
- Knowledge of GPU architectures and CUDA programming
- Knowledge of ML, deep learning and LLM
- Experience working and communicating cross-functionally in a team environment
- roven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
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 Whats App 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.
$58.65/hour 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.
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About Meta

Meta
PublicA social technology company that enables people to connect, find communities, and grow businesses.
10,001+
Employees
Menlo Park
Headquarters
$800B
Valuation
Reviews
3.4
26 reviews
Work Life Balance
2.3
Compensation
4.2
Culture
2.8
Career
3.1
Management
2.1
45%
Recommend to a Friend
Pros
Excellent compensation and benefits
Smart and talented colleagues
Fast-paced and challenging work environment
Cons
Frequent layoffs and job insecurity
Poor leadership and management accountability
High stress and competitive work environment
Salary Ranges
40,175 data points
Mid/L4
Mid/L4 · Data Scientist
3,113 reports
$284,667
total / year
Base
$179,458
Stock
$79,981
Bonus
$25,228
$193,897
$434,902
Interview Experience
6 interviews
Difficulty
4.2
/ 5
Duration
21-35 weeks
Offer Rate
17%
Experience
Positive 17%
Neutral 17%
Negative 66%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Coding Interviews
6
System Design Interview
7
Behavioral Interview
8
Final Loop/Hiring Manager Round
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Live Coding
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