Machine Learning Engineer, Search Infrastructure

As a Machine Learning Engineer on the Search Infrastructure team, you will be instrumental in developing and deploying cutting-edge machine learning models that power Google Search. You'll tackle complex challenges in areas such as information retrieval, ranking, query understanding, and natural language processing. Your work will involve designing, implementing, and optimizing ML pipelines, experimenting with novel algorithms, and collaborating with world-class researchers and engineers to bring innovative solutions to billions of users worldwide. Responsibilities: - Design, develop, and deploy scalable machine learning systems for Google Search. - Research and implement state-of-the-art ML algorithms and techniques. - Optimize ML models for performance, efficiency, and accuracy. - Collaborate with cross-functional teams, including product managers, researchers, and other engineers. - Stay abreast of the latest advancements in ML and NLP. Minimum Qualifications: - Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience. - 2 years of experience in software development or machine learning. - Experience with programming languages such as C++, Java, Python, or Go. Preferred Qualifications: - Master's or Ph.D. in Computer Science, Machine Learning, or a related field. - Experience with large-scale ML systems and distributed computing. - Deep understanding of ML concepts, including deep learning, reinforcement learning, and NLP. - Experience with ML frameworks like TensorFlow or PyTorch.