Principal Machine Learning Infrastructure Engineer, Ads & Discovery

Overview

Principal Machine Learning Infrastructure Engineer on the Ads & Discovery team, building large-scale ads ML infrastructure for recommendation, search, and agentic applications.

What you'll do

• Co-design models and systems at the intersection of model architecture and ML infrastructure, partnering with core modelers, data and AI infrastructure engineers, and product teams.
• Investigate model, data, and systems tradeoffs end to end, from data pipelines and distributed training to low-latency inference and production serving.
• Design efficient KV-cache strategies, apply pruning and quantization, optimize GPU utilization and memory efficiency, and develop custom kernels where needed.
• Lead strategic planning and roadmap execution of scalable, production-ready ML systems including model training, data pipelines, feature engineering and model inference.
• Own the architecture and establish engineering best practices for scalability, reliability, and cost-effectiveness of ML infrastructure (training, serving, features).
• Work closely with data scientists, ML engineers, platform teams, and product stakeholders to design, implement, and operate robust ML platforms.
• Stay abreast of industry trends in machine learning and infrastructure and adopt leading-edge technologies and practices.

What you'll need

• 5+ years of experience designing, building, and deploying large-scale machine learning systems in production environments.
• 3+ years of experience tech leading ML infrastructure engineers.
• Strong communication skills and a collaborative approach to problem solving.
• BS, MS, or Ph.D. in Computer Science, Engineering, or equivalent experience.

Details

• Location: San Mateo, CA, United States (headquarters).
• Work mode: onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday.
• Employment type: full-time, eligible for equity compensation and benefits.
• For US-based roles, the Company may not be able to employ candidates who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.