Sr. Staff Software Engineer, AI Infrastructure at LinkedIn3

Department: EngineeringSeniority in posting: senior

Compensation

$198,000 – $326,000/yr

Setup: Hybrid
Location: Sunnyvale, California
Type: Full-time
Level: staff+
Posted: Sep 25, 2026

Description

LinkedIn is hiring a Sr. Staff Software Engineer for its AI Training Infrastructure team to build and optimize large-scale distributed training and serving infrastructure for recommendation, large language, and computer vision models. The role involves high-performance data I/O, distributed and GPU-based training and inference, observability, containerized pipeline orchestration, open-source contributions, and technical leadership across AI infrastructure initiatives. It is based in Mountain View, California, or Bellevue, Washington, with a hybrid work arrangement, and offers a base salary of $198,000 to $326,000 plus potential bonus, stock, and benefits.

Required Skills

Distributed systems
Deep learning
GPU serving
PyTorch
Technical leadership
Observability

Additional Information

Minimum Education: Bachelor of Science or Bachelor of Arts in Computer Science or a related technical field, or equivalent technical experience
Required Previous Experiences: 5+ years of industry experience in software design, development, and algorithm-related solutions
5+ years of experience programming in object-oriented languages such as Python, C++, Java, Go, Rust, or Scala
2+ years of experience as an architect or in a technical leadership position
5+ years of industry experience leading or building deep learning systems
Hands-on experience developing distributed systems or other large-scale systems
Preferred Qualifications: Master of Science or PhD in Computer Science or a related technical discipline
10+ years of experience in software design, development, and algorithm-related solutions, including at least 5 years in technical leadership
10+ years of experience in an object-oriented programming language such as Python, C++, Java, Go, Rust, or Scala
5+ years of experience with large-scale distributed systems and client-server architectures
Experience building machine learning applications, large language model serving, and GPU serving
Co-author or maintainer of open-source projects
Expertise in machine learning infrastructure, including MLFlow, Kubeflow, and large-scale distributed systems
Expertise in deep learning frameworks and tensor libraries such as PyTorch, TensorFlow, and JAX/FLAX
Translation Company Name: LinkedIn