Staff Machine Learning Engineer 5

Adobe Adobe · Enterprise · San Jose, CA

Staff Machine Learning Engineer at Adobe to design, build, and maintain AI/ML systems for GenStudio. Responsibilities include framing product features as ML tasks, analyzing trade-offs, managing data labeling, organizing datasets, implementing research techniques, handling cold-start scenarios, defining benchmarks, architecting scalable ML systems, and optimizing model development in GPU/TPU environments. Requires 12+ years of experience, expertise in ML/DL, Python, PyTorch, and scalable AI/ML system design.

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. Architect scalable ML systems (e.g., multi-agent, recommender, active learning, multi-stage model training, enterprise search) for both offline and online workflows.
  3. Implement and adapt techniques from academic research and industry papers; evaluate algorithmic trade-offs considering data requirements, latency, and runtime.
  4. Analyze trade-offs across cost, latency, and accuracy while ensuring compliance with UX, privacy, legal, and security constraints.
  5. Optimize model development and deployment in GPU/TPU environments using PyTorch.

Skills

Required

  • Machine Learning
  • Deep Learning
  • model design
  • model optimization
  • model fine-tuning
  • transfer learning
  • Python
  • PyTorch
  • TensorFlow/Keras
  • CUDA
  • Hugging Face
  • JAX
  • scalable AI/ML systems design
  • GPU/TPU environments
  • data engineering
  • dataset management
  • feature engineering
  • data drift
  • high-performance implementation
  • production-grade services

Nice to have

  • GenAI-first applications
  • mentoring senior engineers
  • thought leadership
  • contributions to industry forums, conferences, or open-source communities

What the JD emphasized

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

Other signals

  • design, build, test, and maintain AI/ML-based systems
  • architect scalable ML systems
  • optimize model development and deployment