Machine Learning Engineer

Adobe · Bangalore

onsitefull-time3-6 years

posted 1d

About the Role 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 single model. It'll be measured in a capability you create that the whole team builds on for years. And the problems are real. A few of the things you could own: Revenue that responds to your models. As our growth targets climb, the game shifts from volume to conversion. You'll build propensity and conversion models that decide who we reach and how — work that shows up directly in the numbers the business cares about most. Making sense of Gen AI at scale. Everyone wants to understand how generative AI is really being used. You'll build the models that get us there: anomaly detection, Return of Investment prediction, prompt classification — turning raw signal into insight nobody else has. AI that actually knows the customer. We're building an administration assistant that adapts to who it's talking to. You'll train the persona and personalisation models that make it feel genuinely intelligent — real ML, not prompt-tuning around someone else's LLM. Systems that learn from themselves. You'll design closed-loop models that take outcomes from live initiatives and feed them back to make the next round smarter. You'll have the autonomy of a founder, the backing of an established team, and the reach of Adobe — where the work you ship touches hundreds of millions of people. If you want to be the ML engineer who shaped how a team builds, this is that seat. Key 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. Minimum Qualifications 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 empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager