Machine Learning Engineer 4

Adobe Content Intelligence helps marketers and creators understand what makes their work perform. Our team builds the models and pipelines that analyze images, video, email, and paid social ads — then connect those signals to campaign results. That work powers insights, recommendations, and agent tools used across Adobe's products today.

We're looking for a senior Machine Learning Engineer to own how those systems are designed, built, and shipped. You'll train and improve models yourself — not just plug in models someone else built — and you'll shape the architecture for multi-modal creative intelligence at enterprise scale. If you like turning hard ML problems into production systems that real customers use, we'd love to meet you!

What you'll do

- Design and train models for creative understanding across vision, video, and language

- Build labels and features from LLMs, subject-matter experts, and user activity data

- Deliver pipelines for ingestion, featurization, training, versioning, and inference at scale

- Validate models with offline benchmarks and online A/B tests before release

- Operate production ML on Spark, Kubernetes, and GPU/CPU environments

• You'll work with product managers, research scientists, and engineers across Adobe to connect ML work to customer value — from performance insights to brand-aware recommendations and context for agent workflows.

• You'll mentor other engineers, lead design reviews, and share what you learn through docs, talks, and technical interviews.

What you need to succeed

- Strong Python and PyTorch for model development and deployment

- Deep learning experience across vision, video, NLP, or generative AI (LLM/VLM fine-tuning, embeddings, or RAG)

- End-to-end ML systems: feature engineering, training pipelines, inference, and production monitoring

- Distributed data processing and cloud platforms (Spark, Kubernetes, GCP, AWS, or Azure)

- Clear communication with senior leaders on ML trade-offs and technical direction