Machine Learning Engineer

Adobe is hiring a Machine Learning Engineer in Bangalore.

Responsibilities

• Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences.
• Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning.
• Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/check-pointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent).
• Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs.
• Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization.
• Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and production monitoring.
• Collaborate cross-functionally with data science, product, and platform teams; mentor junior engineers on experimentation rigor, deployment process, and responsible AI.
• Know the latest advances in ML/AI and bring relevant innovations into Adobe's products.

Requirements

• Bachelor’s degree or Master’s degree or equivalent experience in Computer Science, Machine Learning, Data Science, or related field.
• 4 - 8 years of professional experience building and deploying ML solutions at scale.
• Strong programming expertise in Python, with hands-on experience in 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.

About Adobe

Adobe is seeking a Machine Learning Engineer to join the Administration team in Adobe Unified Platform . This group drives the enterprise business for Adobe. This is a rare kind of role: you won't be slotting into a machine that's already running. You'll be the founding ML voice on a team of strong senior engineers who know how to ship, but who are looking to you to set the approach — to decide how models get built, trained, evaluated, and put into production. Your impact won't be measured in a