Senior Staff Machine Learning Engineer, ML Platform

What you'll do

• Design and develop scalable model training and fine-tuning infrastructure for the ML platform.
• Build high-performing machine learning systems from the ground up to support internal teams.
• Develop unified platforms for model inference, agentic AI, and associated data services.
• Implement distributed training at scale using optimization techniques like pruning, compression, and quantization.
• Create tools and infrastructure that enable rapid development and deployment of ML applications.
• Architect machine learning products that adhere to strict privacy commitments and standards.
• Select appropriate technologies and define architectures to solve complex ad network challenges.

What we're looking for

• Experience building shared ML platforms, frameworks, or services used by multiple teams or organizations.
• Deep understanding of the ML lifecycle, including training pipelines, evaluation methodologies, and deployment patterns.
• Deep understanding of deep learning architectures (Transformers, LLMs, DNNs) and training frameworks like TensorFlow or PyTorch.
• Prior experience applying ML at scale in Ads, recommender systems, information retrieval, or related domains.
• Prior experience in distributed training at scale and optimization techniques such as model pruning, compression, quantization, and distillation.
• Prior experience building AI/ML tooling for model fine-tuning and training, and infrastructure at scale.
• Ability to communicate effectively with both technical and non-technical multi-functional teams.
• PhD/MS/BS in Computer Science or related field with 10+ years of industry experience in building ML systems (preferred).