Principal Engineer Ai/ml

Adobe Adobe · Enterprise · San Jose, CA +2

Principal Engineer AI/ML at Adobe, focusing on designing, building, and scaling AI/ML systems for GenStudio. The role involves framing product features as ML tasks, analyzing trade-offs, managing data, implementing research techniques, defining benchmarks, architecting scalable ML systems, and optimizing model deployment. Requires strong software engineering and ML/DL expertise, with experience in Python, PyTorch, and GPU/TPU environments.

What you'd actually do

  1. Design, build, test, and maintain AI/ML-based systems and applications that serve as the backbone of scalable, production-ready technology stacks.
  2. Frame product features as ML tasks (e.g., classification, recommendation, context engineering).
  3. Analyze trade-offs across cost, latency, and accuracy while ensuring compliance with UX, privacy, legal, and security constraints.
  4. Assess data distribution (variance, sampling, drift) and manage data labeling workflows involving LLMs, SMEs, or user-generated activity.
  5. Organize datasets for training, validation, and testing, and engineer high-quality features using normalization, smoothing, and weighting techniques.

Skills

Required

  • 14+ years of experience in software engineering
  • Bachelor's or Master’s degree in Computer Science or a related field (or equivalent experience)
  • Proven expertise in Machine Learning and Deep Learning, including model design, optimization, and fine-tuning.
  • Strong understanding of transfer learning principles and their application in production settings.
  • Proficiency in Python (especially for data workflows)
  • experience with ML/DL frameworks such as PyTorch, TensorFlow/Keras, CUDA, Hugging Face, and JAX.
  • Experience designing and deploying scalable AI/ML systems optimized for GPU/TPU environments.
  • Solid grasp of data engineering concepts—including dataset management, feature engineering, and handling data drift.
  • Ability to balance theoretical ML knowledge with practical, high-performance implementation.
  • Strong understanding of how to transform models into reliable, production-grade services.

Nice to have

  • Experience with building GenAI-first applications.

What the JD emphasized

  • scalable, production-ready technology stacks
  • scalable ML systems
  • production-grade services

Other signals

  • Design, build, test, and maintain AI/ML-based systems and applications
  • Architect scalable ML systems (e.g., multi-agent, recommender, active learning, multi-stage model training, enterprise search)
  • Optimize model development and deployment in GPU/TPU environments