You're a highly technical research engineer with a strong understanding of the latest advancements in AI, especially GenAI - LLMs and Agents You have 5+ years of professional experience in software engineering, GenAI, machine learning, or applied research, with a proven ability to drive high-impact AI initiatives end to end Strong working knowledge of deep learning, machine learning and statistics Some experience in complex SQLs and ETL transformations Experience related to AWS services such as SageMaker, Bedrock, EMR, S3, OpenSearch Service, Step Functions, Lambda, and EC2 Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts Demonstrated ability to design, implement, and scale machine learning workflows (ML OPs); including deployment and delivery of production-ready model APIs Proficiency with at least one machine learning lifecycle platform (Sagemaker, MLFlow, TensorFlow, etc.), orchestration platform (Airflow, Dagster, etc.) and data platform like SnowFlake/DataBricks You have a track record of implementing cutting-edge research into robust, scalable, and well-tested code You bring a strong engineering mindset and write clean, efficient code that performs reliably in production 3+ years experience with AWS or other public cloud platforms (GCP, Azure, etc.) Excellent verbal and written communication skills Experience with Infrastructure-as-Code tools and frameworks Masters degree in computer science, data science, mathematics, or a related field. From the central office to the classroom to the home, PowerSchool supports the entire educational ecosystem as the global leader of cloud-based software for K-12 education.