Senior ML Platform Engineer: Real-Time Fraud & Risk

Adobe; San Jose (CA); On-site; USD 178,000 - 258,000; Full time

Job summary

Adobe is seeking a Senior Software Engineer focused on Data Science and Platform Engineering to build ML models that detect fraud and abuse across Adobe surfaces. You will own the end-to-end ML lifecycle and the production platform, delivering fast, scalable risk decisions at high volume.

You will collaborate with fraud investigators and platform teams, leverage Python/SQL, ML frameworks, and big data tools, and continuously improve detection with new approaches and features.

Qualifications

• Bachelor's or Master's in Computer Science, Statistics, ML, or related — or equivalent experience.
• Deep experience with ML techniques — supervised/unsupervised learning, anomaly detection, ensembles — applied to fraud or risk detection.
• 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.
• Fluent in Python and SQL; comfortable with ML frameworks (PyTorch, TensorFlow, scikit-learn) and a production language (Java, Go, or similar).
• Experience with big data tools like Spark or Databricks for training and serving at scale.
• Strong platform engineering skills: APIs, distributed services, and data pipelines built for scale and low latency.
• Curiosity to understand how abuse actually plays out in a workflow, not just how it looks in aggregate metrics.
• Works well across fraud, platform, and product teams.
• Preferred: real-time scoring systems, device fingerprinting, or using LLMs/agentic AI for fraud detection.
• Experience working on risk mitigation is a plus.

Responsibilities

• 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.
• Turn behavioral, device, and transaction signals into features that sharpen detection.
• 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.
• 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. Keep it fast, reliable, and scalable as usage grows.
• Partner with fraud investigators, Trust & Safety, and platform teams to turn new fraud patterns into new defenses, fast.

Skills

Python

SQL

ML frameworks

Spark

Go/Java

Platform engineering

Education

Bachelor's or Master's in CS/Statistics/ML

Tools

PyTorch

TensorFlow

Job description

Adobe is seeking a Senior Software Engineer focused on Data Science and Platform Engineering to build ML models that detect fraud and abuse across Adobe surfaces. You will own the end-to-end ML lifecycle and the production platform, delivering fast, scalable risk decisions at high volume.

You will collaborate with fraud investigators and platform teams, leverage Python/SQL, ML frameworks, and big data tools, and continuously improve detection with new approaches and features.