Staff Machine Learning Engineer/architect– Agentic AI & Personalization

Adobe Adobe · Enterprise · San Jose, CA

Staff ML Engineer/Architect to build LLM-powered agents for personalization and real-time decisioning systems, architecting end-to-end ML systems including feature pipelines, training, and low-latency inference, and leading MLOps practices. This is a 0->1 opportunity to define agentic AI for enterprise personalization.

What you'd actually do

  1. Build LLM-powered agents for model generation, experimentation, and next-best-action optimization
  2. Develop recommendation, ranking, and real-time decisioning systems
  3. Architect end-to-end ML systems (feature pipelines, training, low-latency inference)
  4. Lead MLOps (CI/CD, monitoring, drift detection, retraining)
  5. Partner with Product to drive measurable business impact

Skills

Required

  • Python
  • ML frameworks (PyTorch, TensorFlow, HuggingFace, etc.)
  • building production ML systems at scale
  • personalization, recommendation systems, or real-time decisioning
  • owning end-to-end ML systems

Nice to have

  • hands-on experience with production grade LLMs and agents

What the JD emphasized

  • autonomous, agent-driven AI systems
  • Agentic Systems
  • 0->1 opportunity
  • LLM-powered agents
  • recommendation, ranking, and real-time decisioning systems
  • end-to-end ML systems
  • agentic AI best practices
  • production ML systems at scale
  • personalization, recommendation systems, or real-time decisioning
  • end-to-end ML systems
  • LLMs and agents

Other signals

  • building LLM-powered agents
  • developing recommendation, ranking, and real-time decisioning systems
  • architecting end-to-end ML systems
  • leading MLOps
  • 0->1 opportunity to define how agentic AI powers enterprise personalization