Staff Applied AI Engineer, Enterprise Genai

Scale AI Scale AI · Data AI · San Francisco, CA · Enterprise Engineering

Scale AI is seeking a Staff Applied AI Engineer to build advanced AI agents for enterprise clients using their Generative Platform (SGP). The role involves owning and optimizing AI solutions, leveraging SGP for multimodal functionality and tool-calling, gathering business requirements, collaborating with clients, and pushing production code in customer and Scale codebases. The ideal candidate has 7+ years of experience, a strong engineering background, and familiarity with data-driven ML model iteration and cloud environments.

What you'd actually do

  1. Own, plan, and optimize the AI behind our Enterprise customer’s deepest technical problems
  2. Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
  3. Have experience gathering business requirements and translating them into technical solutions
  4. Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
  5. Push production code in multiple development environments, writing and debugging code directly in both our customer’s and Scale’s codebases.

Skills

Required

  • 7+ years of full-time engineering experience, post-graduation
  • A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client’s business goals
  • Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background.
  • Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
  • Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
  • Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Nice to have

  • Strong knowledge of software engineering best practices
  • Have built applications taking advantage of Generative AI in real, production use cases
  • Familiarity with state of the art LLMs and their strengths/weaknesses

What the JD emphasized

  • Own, plan, and optimize the AI behind our Enterprise customer’s deepest technical problems
  • build the most advanced AI agents across the industry
  • Push production code in multiple development environments

Other signals

  • building complex agents for enterprises
  • applying foundation genomic models
  • creating transformative AI experiences