Job Description Summary:
Join and build the next generation of AI Personalization platform in client's Consumer Machine Learning team. Take AI Stack to the next level, and create the future of the Search stack on the client's App! As a Machine Learning Engineer in Consumer ML Ops team, you will be responsible for designing, developing, and maintaining recommendation infrastructure on client Stacks and deploying solutions that impact hundreds of millions of consumers' personalized experiences.
Get involved in Google Vertex (any cloud will do) AI solutions Stack to bring cutting-edge cloud solutions into existing stacks, such as AutoML, custom training, BQML, real-time inferencing, features stores, GenAI, etc. You will be working closely with data science team to ensure that models are deployed, monitored, and scaled efficiently.
Optimization project for a financial payment platform's consumption scenario recommendation system, aiming to enhance personalized recommendation experiences.The project involved upgrading recommendation algorithm services, rebuilding data pipelines, and integrating with upstream and downstream systems.
Requirements:
• Bachelors / Master’s degree or equivalent experience in a quantitative field (Computer Science, Mathematics, Statistics, Engineering, Artificial Intelligence, etc.)
• At least 4 years experiencecs, experienced with Java, Spring;
• Good knowledge and experience with Cloud provider such as GCP, AWS, Azure, Huawei, Alibaba to build enterprise level solutions
• Experience with containerization technologies such as Docker and Kubernetes. Familiarity with DevOps best practices and tools such as Git, Jenkins
• Good English speaking and writing
