Machine Learning Engineer 3

Overview

Machine Learning Engineer to build end-to-end deep learning systems that protect Adobe’s ecosystem from fraud and account misuse.

What you'll do

• Build and train deep learning models from scratch for long behavioral event sequences.
• Own the training stack from event tokenization through temporal/positional embeddings and pretraining, then fine-tuning.
• Train large models on GPU infrastructure with mixed-precision and distributed strategies.
• Build and optimize feature pipelines on Databricks and Spark.
• Translate prototypes into production ML systems with scalable, reliable, and observable deployment.
• Contribute to MLOps practices including experiment tracking, model versioning, CI/CD, retraining, and monitoring.

What you'll need

• 5+ years of professional experience building and deploying ML solutions at scale.
• Python programming expertise.
• Hands-on experience with PyTorch, TensorFlow, or similar frameworks.
• Deep understanding of the end-to-end ML lifecycle from data collection to deployment and monitoring.
• Strong grasp of model optimization, inference efficiency, and production system integration.
• Bachelor’s degree or Master’s degree or equivalent experience in relevant fields.

Nice to have

• Experience in fraud detection, anomaly detection, or behavioral modeling.

Details

• Location: Bangalore.