Staff Genai/ml Engineer (emerging Tech & AI Automation) Project Hire

Disney Disney · Media · Burbank, CA +1

Staff GenAI/ML Engineer role focused on designing, prototyping, and building GenAI-enabled solutions and platform components for enterprise use cases. This role involves integrating LLMs, RAG, fine-tuning, and prompt engineering, as well as contributing to technical strategy and MLOps best practices.

What you'd actually do

  1. Lead design and rapid prototyping of GenAI-enabled solutions (chatbots, summarizers, copilots) to explore and validate high-impact business opportunities.
  2. Evaluate and integrate LLMs and modern GenAI techniques (e.g., RAG, fine-tuning, prompt engineering, embeddings, vector databases) into enterprise use cases.
  3. Lead architecture discussions, conduct model performance evaluations, and implement best practices in MLOps and GenAI infrastructure.
  4. Design and build reusable PoCs, pilots, and platform components leveraging modern GenAI/ML frameworks.
  5. Embed directly with teams including product managers, researchers, and engineering teams to co-develop innovative, robust and scalable GenAI solutions—translating context-rich insights into technical designs and working prototypes that drive meaningful innovation.

Skills

Required

  • Python
  • system design
  • scalable architecture
  • PyTorch
  • TensorFlow
  • HuggingFace Transformers
  • LangChain
  • prompt engineering
  • RAG pipelines
  • LLM evaluation
  • fine-tuning LLMs
  • scalable AI/ML systems
  • NoSQL
  • graph/vector databases
  • relational databases
  • MLOps
  • MLflow
  • Kubeflow
  • Docker
  • Kubernetes
  • AWS
  • Azure
  • GCP

Nice to have

  • R&D or innovation-focused environments
  • fast-paced prototyping
  • ambiguous problem spaces
  • building tools or platforms that enable enterprise-wide adoption of AI/ML technologies
  • open source contributions
  • patents
  • publications in GenAI or ML

What the JD emphasized

  • 7+ years of experience in software engineering or ML/AI engineering, with 2+ years hands-on with GenAI or LLM technologies.
  • Hands-on experience deploying solutions in cloud environments such as AWS, Azure, or GCP.
  • Proven experience working on AI/ML, GenAI, automation, or advanced data platform initiatives in enterprise or R&D settings.
  • Deep knowledge of GenAI techniques including prompt engineering, RAG pipelines, LLM evaluation and fine-tuning LLMs.
  • Strong understanding of MLOps best practices and experience with tools like MLflow, Kubeflow, Docker, and Kubernetes.

Other signals

  • design and rapid prototyping of GenAI-enabled solutions
  • Evaluate and integrate LLMs and modern GenAI techniques
  • Design and build reusable PoCs, pilots, and platform components