Staff Software Engineer, AI/ML, Cloud IAM, Dataset and Model Training

Responsibilities: Design and scale training data pipelines using telemetry, policy graphs, and synthetic data with de-noising Train and optimize ML models for Intelligent IAM focusing on access-risk scoring, anomaly detection, and least-privilege recommendations Build explainability and calibration layers for risk scores and route uncertain cases to human review or static rules Collaborate with security engineers to identify IAM edge cases and learn subtle privilege boundaries Establish evaluation benchmarks and online monitoring to prevent model drift Optimize models for low-latency serving in Google Cloud Own end-to-end ML lifecycle: data curation, benchmarking, and deployment into high-reliability services

Key requirements: Bachelor’s degree or equivalent practical experience 8 years of software development experience 5 years of experience testing and launching software products 3 years of experience with software design and architecture 5 years of experience in one or more: Speech/audio, reinforcement learning, ML infrastructure, or another ML field 5 years of experience leading ML design and optimizing end-to-end ML lifecycle leadership cross-functional collaboration problem-solving PyTorch JAX scikit-learn