Senior Machine Learning Systems Engineer

Design end-to-end MLOps patterns to boost ML development velocity Build a graph ML platform enabling scalable model iterations Tune performance: training time, efficiency, and GPU costs Optimize batch data processing with Beam, Spark, Ray Data Architect pipelines for billions of graph nodes and edges 5+ years in ML infrastructure incl training and deployments Hands-on ML optimization: memory and GPU profiling Cloud ML platforms: GCP BigQuery, Google Cloud Storage, Terraform Experience with MLOps tools: MLflow or Wandb Proficiency in Python, PyTorch, TensorFlow Distributed training: Ray and Kubernetes Graph databases: Neo4j, JanusGraph, TigerGraph Equity 401(k) with employer match Medical, dental, and vision insurance Generous vacation and parental leave Accommodations for disabilities