Sr / Staff Machine Learning Engineer

Overview In this role, you will design, build, and scale production ML systems for Adobe’s security domain, turning research into reusable capabilities. You will work at the intersection of cybersecurity, large-scale data, and AI, shaping architectures used across security analytics, anomaly detection, and threat investigation. You’ll own the ML lifecycle—from feature engineering to deployment and retraining—while collaborating with data, platform, and security engineers. This position offers meaningful impact through advanced AI tooling and security-focused applications. ResponsibilitiesArchitect end-to-end ML systems for high-volume security dataOwn the ML lifecycle from feature engineering to deployment and retrainingBuild LLM and agentic AI capabilities for security investigation (RAG)Design evaluation frameworks to measure model quality and analyst trustScale data pipelines in partnership with data/platform engineersMentor engineers and influence technical directionCollaborate with data, platform, and security teams across Adobe Key requirementsProduction ML systems experience from experimentation to sustained operation at scaleStrong background training models with PyTorch and transformers (behavioral modeling, anomaly detection)Experience with distributed compute (Spark) and cloud platforms (AWS)MLOps experience (e.g., MLflow)Experience building with LLMs/generative AI and production behavior assessmentStrong Python and SQL skills with good software engineering practices (testing, code review)MS or PhD in computer science, ML, or related field, or equivalent practical experienceCollaborative mindsetMentoring and technical leadershipCross-team communicationPyTorchTransformersAnomaly detection