ApacheAWSCloudGoogle Cloud PlatformJavaPythonPyTorchRayScalaSparkAIMachine LearningMLGenerative AILarge Language ModelsHugging FaceApache SparkGCPGoogle CloudAgile
About this role
Role Overview
contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development
promote and role-model best practices of ML systems development, testing, evaluation
lead collaborations and align across PZN to integrate and A/B test mid-term signals in various recommendation systems
Requirements
strong background in machine learning
expertise in statistics and optimization, especially in sequential models, transformers, generative AI and large language models
hands-on experience with large cross-collaborative machine learning projects
hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages
experience with PyTorch, Ray, Hugging Face and related tools
experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark
cloud platforms like GCP or AWS
care about agile software processes, data-driven development, reliability, and disciplined experimentation