Senior Software Engineer

Adobe Adobe · Enterprise · San Jose, CA

Senior Software Engineer to build and maintain ML models for fraud detection and the low-latency platform serving them at scale for Adobe's Risk Platform. Responsibilities include data engineering, model development, real-time inference, and platform ownership.

What you'd actually do

  1. Own the ML lifecycle end-to-end — data engineering, offline model development, and real-time inference — building the models that detect and stop fraud and abuse across our surfaces.
  2. Turn behavioral, device, and transaction signals into features that sharpen detection.
  3. Track precision, recall, false positives, and business impact, and experiment with new approaches (including LLMs and agentic AI) to catch more while reviewers do less.
  4. Own the platform that serves those models in production, from APIs and SDKs to feature stores and the integration points that make onboarding new surfaces turnkey.
  5. Keep it fast, reliable, and scalable as usage grows.

Skills

Required

  • Python
  • SQL
  • ML frameworks (PyTorch, TensorFlow, scikit-learn)
  • production language (Java, Go, or similar)
  • big data tools (Spark or Databricks)
  • platform engineering skills (APIs, distributed services, data pipelines)
  • ML techniques (supervised/unsupervised learning, anomaly detection, ensembles) applied to fraud or risk detection

Nice to have

  • real-time scoring systems
  • device fingerprinting
  • using LLMs/agentic AI for fraud detection
  • risk mitigation experience

What the JD emphasized

  • 5+ years building production ML systems and scalable backend services
  • Comfortable owning a model's full lifecycle in production — monitoring, retraining, and tuning as fraud patterns shift.

Other signals

  • ML models for fraud detection
  • low-latency serving platform
  • end-to-end ML lifecycle ownership
  • production ML systems