Machine Learning Engineer, Search Relevance

As a Machine Learning Engineer on the Search Relevance team, you will be at the forefront of developing and deploying cutting-edge ML models that power Google Search. You'll work on challenging problems related to understanding user intent, ranking search results, and personalizing the search experience. This role involves designing, implementing, and evaluating ML systems, collaborating with researchers and product managers, and contributing to the continuous improvement of Google Search. **Responsibilities:** - Design, develop, and deploy large-scale machine learning models for search relevance. - Collaborate with researchers to translate novel algorithms into production systems. - Analyze model performance, identify areas for improvement, and implement optimizations. - Develop and maintain robust ML infrastructure and tooling. - Stay up-to-date with the latest advancements in ML and information retrieval. **Minimum Qualifications:** - Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience. - 3 years of experience in software development or machine learning. - Experience with Python and at least one ML framework (e.g., TensorFlow, PyTorch). **Preferred Qualifications:** - Master's or PhD in Computer Science, Machine Learning, or a related field. - Experience with large-scale distributed systems and data processing. - Strong understanding of information retrieval, natural language processing, or deep learning. - Experience with large-scale model training and deployment. Google offers competitive salaries, comprehensive benefits, and opportunities for professional growth in a dynamic and innovative environment.