2 days ago
Base Salary
$347k - $403k/yr
Responsibilities
- Define and own the architecture of critical machine learning systems, including training pipelines, inference infrastructure, and feature engineering platforms.
- Solve complex ML systems challenges involving model quality, training efficiency and stability, serving latency and correctness, and data integrity.
- Develop extensible ML frameworks, modeling standards, and engineering practices across multiple organizations.
- Lead cross-functional technical strategy and multi-year roadmaps for machine learning initiatives.
- Apply AI-native workflows and tooling to accelerate model development and automate evaluation pipelines.
- Define metrics and data-driven decision-making principles connecting model performance to business outcomes.
- Identify reliability, privacy, and integrity risks and build technical safeguards for responsible AI deployment.
- Mentor engineers on ML systems design, model debugging, and production-grade AI systems.
- Drive performance improvements across training, data loading, model serving, and hardware utilization.
- Influence the ML engineering community through publications, design frameworks, and cross-industry engagement.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- 12+ years of experience designing, building, and deploying large-scale machine learning systems in production environments.
- Experience architecting end-to-end ML platforms covering data pipelines, distributed training, model evaluation, and low-latency inference serving.
- Experience resolving complex cross-system ML failures involving model quality, training stability, feature consistency, and serving correctness.
- Experience defining technical strategy and aligning multiple engineering teams and cross-functional stakeholders.
- Experience communicating complex ML system designs and trade-offs to technical and non-technical audiences, including executive leadership.
- Preferred: experience integrating AI tools and building AI-native developer tooling or automation to improve ML experimentation and deployment.
- Preferred: ongoing AI skill development, including prompt/context engineering or agent orchestration.
- Preferred: industry-recognized contributions such as publications, open-source frameworks, or widely adopted architectural patterns.
- Preferred: ML experience in ranking, recommendation, generative AI, computer vision, or natural language understanding.
- Preferred: experience with foundation model training, fine-tuning, or inference optimization across distributed hardware clusters.
- Preferred: experience implementing responsible and ethical AI practices, including risk assessment, bias mitigation, and quality reviews.
Benefits
- The posting lists bonus, equity, and benefits in addition to the stated base salary.
Categories
About Meta
Meta builds social platforms and communication apps—including Facebook, Instagram, WhatsApp, and Messenger—and develops AR/VR hardware and software such as Quest to power immersive computing. It monetizes primarily through advertising tools for businesses, with additional revenue from devices and services, and operates a massive global infrastructure. Founded in 2004 and headquartered in Menlo Park, California, Meta Platforms, Inc. is a public company traded on Nasdaq under the ticker META.