Senior Staff Machine Learning Engineer, ML Platform

What you'll do

• Design and develop model training and fine-tuning infrastructure at scale.
• Build a self-serve, unified platform for training, inference, and agentic AI.
• Develop high-performing machine learning systems from the ground up to support multiple teams.
• Implement distributed training techniques including pruning, compression, quantization, and distillation.
• Create tools and infrastructure for large-scale model fine-tuning and deployment.
• Architect ML solutions that adhere to strict privacy commitments and data standards.
• Develop infrastructure supporting LLM pre-training, supervised fine-tuning, and inference.

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 like Transformers, LLMs, and DNNs using TensorFlow or PyTorch.
• Prior experience applying ML at scale in ads, recommender systems, information retrieval, or related domains.
• Experience in distributed training at scale and optimization techniques such as pruning, compression, quantization, and distillation.
• Experience building AI/ML tooling for model fine-tuning and infrastructure at scale.
• Experience with privacy-preserving ML, LLM training and inference, and Agentic AI.
• A PhD, MS, or BS in Computer Science or a related field with 10+ years of industry experience in building ML systems.