採用
Required Skills
C++
C
Python
High Performance Computing
Distributed Systems
We are looking for software engineers to help scale and improve the efficiency of large AI training and inference for HW accelerators. A core part of this is optimising collective operations to enable optimised network utilisation for data sharing.
This is an opportunity to work within a highly skilled team, collaborating with a large set of cross-functional partners and help bringing next generation large cluster architectures to life.
Software Engineer
- AI/HPC Specialist Responsibilities:
- Work on collective communications stacks to optimise networking operations, leading to improved AI inference and training model performance
- Drive implementation of latency and bandwidth critical networking operations, as well as out-of-band signalling
- Debug custom and third party multi-host, accelerator enabled AI platforms
- Software development using C++/C and Python
- Work closely with other teams to deliver impact
- develop & improve features and innovations
- Extend and optimize large scale learning collective operations
Minimum Qualifications:
- 3+ years of experience developing in C++/C and Python
- Experience with High Performance Computing/Networking or AI systems applications frameworks
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Specialized experience in one or more of the following machine learning/deep learning domains: Hardware accelerators, AI Infrastructure, or high performance networking
- Solid experience in debugging of distributed systems, revision control systems, testing, and CI pipelines
Preferred Qualifications:
- Experience and understanding of AI/HPC systems
- Deep understanding of the transport stack (e.g. RDMA/RoCE, Infiniband, TCP/IP), its constraints and performance measures and how transport considerations enable the collective communications stack
- Experience in one or more of the following machine learning/deep learning domains: hardware accelerators, AI Infrastructure, and/or high performance computing (HPC), particularly pertaining to interconnect and collective communications stacks
- Familiarity with relevant tools, libraries, and frameworks (like Py Torch, NCCL, MPI, CUDA)
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.
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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