Machine Learning Engineer

• Lead the end-to-end ML model lifecycle: identify machine learning opportunities through data and metric analysis, define and track KPIs, and ship iterations aligned with product and business goals.
• Design, develop, and maintain ML pipelines, including feature engineering, model training, deployment, and monitoring.
• Implement scalable inference services and APIs for real-time and batch predictions.
• Improve model accuracy, inference speed, and robustness through experimentation, hyperparameter tuning, and feature optimization.
• Ensure reliability through comprehensive automated testing, observability, and reproducibility of ML experiments.
• Mentor junior engineers, lead code and model reviews, and contribute to architectural decisions and technical documentation.
• Collaborate with cross-functional teams across product, engineering, and operations and with teams in the US and Japan to deliver high-impact ML solutions at global scale.
• Architect and operate highly scalable ML services and pipelines to support rapid user and product growth in the US market.
• Leverage large language models (LLMs) and generative AI to enhance search recall, content understanding, and overall user experience.
• Optimize experimentation frameworks to accelerate product iteration and innovation.

Software Engineer, Machine Learning

Senior Machine Learning Engineer, Vehicle Perception

MLOpsエンジニア, Perception

AIエンジニア

MLOps Engineer

AI/Machine Learning Engineer