Machine Learning Research Engineer, NLP, Input Experience

What you'll do

• Develop and evolve data, tooling, modeling, and evaluation pipelines using agentic harnesses.
• Build and refine personalized agent trajectory pipelines for data and evaluation across synthetic personas and languages.
• Implement state-of-the-art ML playbooks to scale features like Writing Tools, Summarization, and Smart Actions.
• Manage the full ML product lifecycle including problem formulation, fine-tuning, and automated evaluation.
• Curate, filter, and synthesize high-quality training datasets at a global scale.
• Develop models for agentic workflows, tool calling, and advanced reasoning techniques.
• Bridge the gap between raw model performance and production-ready features while ensuring privacy and performance metrics.
• Maintain and manage complex, large-scale codebases with an emphasis on high-quality, testable code.

What we're looking for

• Master's or PhD in Computer Science, Electrical Engineering, Physics, Statistics, or a related field (or equivalent practical experience).
• Prior experience with technical leadership or engineering management.
• Strong foundation in Data Science and the ML stack.
• Familiarity with the product ML/NLP lifecycle.
• Familiarity with techniques such as SFT, RLHF, Data Synthesis, Parameter-Efficient Fine-Tuning, and LLM-judge evaluation.
• Excellent communication skills.
• Experience deploying large ML models for real-world products and leading high-performing teams (preferred).
• Experience curating, filtering, and synthesizing high-quality training datasets at scale (preferred).