8 hours ago
Base Salary
$219k - $301k/yr
Responsibilities
- Identify and solve complex AI systems challenges spanning model training, inference optimization, and large-scale deployment pipelines.
- Architect and own reliable AI infrastructure foundations that support multiple teams building and iterating on machine learning models at scale.
- Define technical strategy and roadmaps for AI platform capabilities across engineering, research, and product organizations.
- Drive multi-year AI initiatives, establish organization-level metrics, and align priorities across multiple teams.
- Create testing frameworks, verification standards, and architectural practices that improve model correctness and reliability.
- Diagnose systemic performance and reliability issues across data ingestion, feature engineering, model serving, and real-time inference.
- Translate machine learning research advances into production systems and measurable product improvements.
- Mentor engineers and serve as a technical advisor on AI systems design, debugging, and engineering practices.
- Evaluate emerging AI technologies and collaborate with legal, policy, privacy, security, and compliance teams on responsible deployment safeguards.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- At least 3 years of software engineering experience focused on AI, machine learning systems, or large-scale distributed systems supporting model training and inference.
- Experience architecting and owning production AI or machine learning platforms at scale, including reliability, performance, and system evolution.
- Experience defining technical strategy and executing across multiple engineering teams while influencing roadmaps and gaining cross-functional alignment.
- Experience debugging systemic AI pipeline failures spanning model behavior, data quality, and infrastructure layers.
- Experience establishing engineering standards, architectural patterns, and verification practices for AI development.
- Preferred: experience publishing or productionizing novel machine learning, ML systems, or AI safety and reliability approaches.
- Preferred: experience with foundation model training infrastructure, distributed training, mixed-precision optimization, or model parallelism.
- Preferred: experience with inference optimization techniques including quantization, distillation, speculative decoding, or accelerator kernel development.
- Preferred: experience collaborating with AI policy, privacy, or integrity teams on responsible AI safeguards.
Benefits
- Annual base salary of $219,000/year to $301,000/year, plus bonus, equity, and benefits.
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.