Software Engineer, Machine Learning

Meta Careers; Menlo Park, Northern (CA, KY); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Meta is seeking a distinguished Software Engineer with deep machine learning expertise to drive transformative advances across Meta's AI-powered products and platforms. In this role you will operate at the intersection of foundational ML research and large-scale production systems, shaping the technical direction of machine learning infrastructure, modeling, and applied AI across the organization.

You will identify and solve the hardest ML systems challenges, define architectural standards, and

Qualifications

• Proven ability to design and scale ML systems.
• Experience with training pipelines and inference infrastructure.
• Comfort leading cross-functional ML initiatives.

Responsibilities

• Define and own the technical architecture of critical ML systems, including model training pipelines and inference infrastructure.
• Identify and solve the most complex ML systems challenges across product areas.
• Develop and establish extensible ML frameworks and engineering practices.
• Lead cross-functional technical strategy for ML initiatives and multi-year roadmaps.
• Apply AI-native workflows to accelerate model development and evaluation pipelines.
• Define metrics and data-driven decision-making principles for long-term ML projects.

Skills

ML systems

Distributed training

Model serving

Architectural design

Job description

# Software Engineer, Machine LearningMenlo Park, CA Artificial Intelligence+ 6 moreApply nowMeta is seeking a distinguished Software Engineer with deep machine learning expertise to drive transformative advances across Meta's AI-powered products and platforms. In this role, you will operate at the intersection of foundational ML research and large-scale production systems, shaping the technical direction of machine learning infrastructure, modeling, and applied AI across the organization. You will identify and solve the hardest ML systems challenges, define architectural standards, and leverage AI-native approaches to unlock step-change improvements in how Meta builds and deploys intelligent systems at global scale.---## Software Engineer, Machine Learning Responsibilities* Define and own the technical architecture of critical machine learning systems, including model training pipelines, inference infrastructure, and feature engineering platforms, ensuring reliability and scalability across billions of users* Identify and solve the most complex ML systems challenges across multiple product areas, including issues that span model quality, training efficiency, serving latency, and data integrity* Develop and establish extensible ML frameworks, modeling standards, and engineering practices that drive consistency and velocity across multiple engineering organizations* Lead cross-functional technical strategy for machine learning initiatives, aligning research, infrastructure, and product teams around multi-year roadmaps that balance short-term delivery with long-term architectural health* Apply AI-native workflows and tooling as a force multiplier to accelerate model development cycles, automate evaluation pipelines, and expand the scope of what engineering teams can deliver* Define new metrics and data-driven decision-making principles for long-term ML projects, connecting model performance signals to organization-level business outcomes