Staff AI Infrastructure Engineer – Scalable ML Platforms

LinkedIn; Mountain View (CA); Hybrid; USD 175,000 - 287,000; Full time

Job summary

LinkedIn is seeking a Staff Software Engineer to join the AI Training Infra team in a hybrid role, working on next‑gen training, feature engineering, and serving infrastructure. You will optimize performance, collaborate with open‑source projects, and mentor teammates while advancing large-scale AI platforms.

The role emphasizes distributed systems, GPU‑based inference, and scalable data pipelines across countless applications, with a focus on collaboration and innovation.

Qualifications

• Bachelor’s degree in computer science or related technical discipline or equivalent practical experience.
• 4+ years of experience in the industry with leading/building deep learning systems.
• 4+ years of experience with Java, C++, Python, Go, Rust, C# and/or Scala or other functional languages.
• Hands-on experience developing distributed systems or other large-scale systems.

Responsibilities

• Own the technical strategy for broad or complex requirements beyond the direct team.
• Design, implement, and optimize large-scale distributed serving or training for recommendations and LLMs.
• Improve observability and developer productivity across systems.
• Mentor engineers and help build a fast-growing AI infrastructure team.
• Collaborate with open-source communities (e.g., PyTorch, HuggingFace, DeepSpeed).
• Act as tech-lead for key AI infrastructure initiatives and future platforms.

Skills

Java

C++

Python

Go

Rust

C#

Scala

Functional languages

Education

Bachelor’s Degree in Computer Science or related technical discipline

Tools

PyTorch

TensorFlow

JAX/FLAX

DeepSpeed

HuggingFace

CUDA

cuDNN

Spark

Flink

Beam

Job description

LinkedIn is seeking a Staff Software Engineer to join the AI Training Infra team in a hybrid role, working on next‑gen training, feature engineering, and serving infrastructure. You will optimize performance, collaborate with open‑source projects, and mentor teammates while advancing large-scale AI platforms.

The role emphasizes distributed systems, GPU‑based inference, and scalable data pipelines across countless applications, with a focus on collaboration and innovation.