Principal Machine Learning Engineer - Evisort AI

Workday Workday · Enterprise · Seattle, WA +1

Workday is seeking a Principal Machine Learning Engineer to join the Evisort AI team, focusing on Document Intelligence and Contract Intelligence. The role involves developing tailored user experiences using LLMs and Knowledge Graphs, delivering ML solutions across Workday's product ecosystem, and deploying new AI products at scale. This position requires extensive experience in ML frameworks, production ML systems, LLMs, and cloud platforms, with a strong emphasis on product development and team leadership.

What you'd actually do

  1. help develop tailored user experiences using advanced LLMs, Knowledge Graphs, personalization, and predictive analysis
  2. collaborate with other engineers to deliver ML solutions across Workday’s product ecosystem
  3. utilize software and data engineering stacks to enable training, deployment, and lifecycle management of various ML models
  4. develop and deploy new products at scale
  5. leverage Workday’s vast computing resources on rich datasets to deliver transformative value to our customers

Skills

Required

  • Pytorch
  • TensorFlow
  • AWS
  • GCP
  • large language models (LLMs)
  • text generation models
  • graph neural network models
  • statistical analysis
  • unsupervised and supervised machine learning algorithms
  • natural language processing
  • information retrieval
  • recommendation system use cases
  • leading, mentoring, and/or managing ML Engineering teams
  • product development
  • software engineering
  • data engineering

Nice to have

  • Master’s or PhD
  • RAG
  • autonomous agents
  • orchestration frameworks

What the JD emphasized

  • 10+ years experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation
  • 6+ years of professional experience in building services to host machine learning models in production at scale
  • 3+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
  • Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement
  • Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation
  • Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases
  • Professional experience in independently solving ambiguous, open-ended problems and technically leading teams

Other signals

  • powers Document Intelligence AI
  • build AI first products
  • develop and deploy new products at scale
  • advanced LLMs, Knowledge Graphs, personalization, and predictive analysis
  • deliver ML solutions across Workday’s product ecosystem
  • enable training, deployment, and lifecycle management of various ML models