Senior Machine Learning Engineer

Zendesk Zendesk · Enterprise · Lisbon, Portugal

Senior Machine Learning Engineer to build and ship LLM-powered applications, including agent architectures and evaluation frameworks, on solid data foundations. The role involves end-to-end ownership from identifying needs to production deployment and iteration, with a focus on driving business outcomes and stakeholder collaboration.

What you'd actually do

  1. Own business metrics (e.g. churn reduction, AI attach rate, seller productivity) and form an opinionated point of view on what we should build next to move them
  2. Define success criteria for the intelligent systems you ship, measure whether they're working for users, and iterate until they are
  3. Design, build, and evaluate LLM-powered applications - agents, RAG systems, text-to-SQL, recommendation engines - owning the full lifecycle from prototype to production
  4. Establish feedback loops for intelligent systems: instrument, measure outcomes, learn what's working, and continuously improve
  5. Develop Python backend services and APIs that connect AI capabilities with modern web applications

Skills

Required

  • 3+ years' experience in Data Science, Machine Learning, or a related field
  • Hands-on experience building and evaluating LLM-powered applications (agents, ML models, or similar)
  • Understanding of agent architectures, prompt engineering, and evaluation frameworks
  • Strong Python programming skills for both AI application development and backend services/APIs
  • Strong SQL skills and experience with cloud data warehouses
  • Familiarity with web development concepts and backend API design

Nice to have

  • Experience with Snowflake, dbt, Airflow, or similar data infrastructure tools
  • Experience with AI-assisted development workflows (Claude Code, Cursor, Copilot, or similar)
  • Experience with frontend technologies and UX design, particularly React
  • advanced degree is highly preferred
  • Experience with AI-assisted development workflows (Claude Code, Cursor, or similar)
  • Experience with frontend technologies and UX design, particularly React

What the JD emphasized

  • build and ship LLM-powered applications
  • own problems end-to-end
  • measuring whether they work
  • iterate based on what you learn
  • build and evaluate LLM-powered applications
  • owning the full lifecycle from prototype to production
  • Establish feedback loops
  • measure outcomes
  • continuously improve
  • Experience owning business outcomes through intelligent systems
  • shipped an ML model, recommendation engine, or AI feature
  • established feedback loops
  • learned what's working
  • continuously improved it based on user impact
  • Hands-on experience building and evaluating LLM-powered applications

Other signals

  • LLM-powered applications
  • agent architectures
  • evaluation frameworks
  • production ML systems
  • end-to-end ownership