Staff Software Engineer, Core ML Platforms

Meta; Bellevue (WA); On-site; USD 184,000 - 257,000; Full time

Job summary

Meta is seeking a Staff Software Engineer for the Core Machine Learning team to architect and deliver high-impact ML platform capabilities, spanning training infrastructure, model serving, feature pipelines, and AI-accelerated tooling. You will enable thousands of engineers to build and ship state-of-the-art models at scale.

You will mentor engineers, drive architectural decisions, and partner with research, product engineering, and infrastructure teams to advance our ML infrastructure roadmap.

Qualifications

• 8+ years of software engineering experience focused on ML systems, infra, or large-scale distributed systems.
• Experience designing production ML systems such as distributed training frameworks, model serving, or large-scale feature pipelines.
• Experience leading major technical initiatives from design through production with cross-team coordination.
• Experience with performance analysis and optimization of ML training or inference workloads, including profiling and instrumentation.
• Experience communicating technical decisions in writing to both engineers and non-engineers through design docs or postmortems.

Responsibilities

• Architect and own large-scale ML infrastructure systems across training, serving, and feature pipelines.
• Lead the technical design and implementation of foundational ML platform components.
• Drive end-to-end delivery of major ML infra initiatives with cross-team coordination.
• Identify and resolve performance bottlenecks in ML training and inference systems.
• Mentor engineers on ML systems design and drive architectural decisions.

Skills

System design

Large-scale ML infra

Distributed systems

Mentoring

Technical leadership

Education

Bachelor's degree in CS or related field

Tools

PyTorch

TensorFlow

Ray

Job description

Meta is seeking a Staff Software Engineer for the Core Machine Learning team to architect and deliver high-impact ML platform capabilities, spanning training infrastructure, model serving, feature pipelines, and AI-accelerated tooling. You will enable thousands of engineers to build and ship state-of-the-art models at scale.

You will mentor engineers, drive architectural decisions, and partner with research, product engineering, and infrastructure teams to advance our ML infrastructure roadmap.