Backend Engineer, Applied Machine Learning Platform

About The Team The Applied Machine Learning (AML) team is seeking a Machine Learning Platform Engineer to develop and maintain our machine learning platform. The platform supports deep learning models for code development, testing, training scheduling, model deployment, and other core business functions. The team oversees the company's critical machine learning platform and serves as a foundation for recommended advertising and search. Here, you can work on recommended systems and distributed training of large-scale deep learning models. We welcome candidates interested in machine learning platform engineering and with excellent engineering capabilities to join our team. If you love challenges and want to develop in the innovation field, please submit your application as soon as possible. What you'll do - Design, develop, and maintain core functions of the machine learning platform, including data processing, feature engineering, model training, and model deployment. - Build efficient, scalable data processing and computing processes to ensure platform stability and performance. - Collaborate with data scientists and machine learning engineers to understand their requirements and provide tool and technical support. - Work closely with system administrators and software engineers to ensure smooth platform integration with other systems. - Responsible for managing and monitoring the operation of the machine learning platform and troubleshooting any platform-related issues. - Continuously track and evaluate emerging technologies and tools and provide suggestions for platform improvements and development. Minimum Qualifications - Bachelor's or above degree in computer science, software engineering, or a related field with 1+ years of relevant experience - Possess solid software engineering skills and be proficient in developing using common programming languages (such as Python, Java, or C++). - In-depth understanding of distributed computing and principles and technologies of large-scale data processing, familiar with related open source tools and frameworks (such as Hadoop, Spark, etc.). - Demonstrate understanding of cloud computing and containerization technologies such as AWS and Docker. - Enthusiastic about learning new technologies and solving complex problems, passionate about engineering challenges. Strong analytical and problem-solving skills, ability to quickly understand and solve engineering problems. Preferred Qualification - A preference for candidates with knowledge and experience in machine learning and deep learning, but it is not required. We value candidates' engineering capabilities and overall quality more.