Senior Machine Learning Engineer

Senior Machine Learning Engineer

Zendesk

Lisbon, Portugal

Role Overview

As an ML Engineer, you will build and ship LLM-powered applications on solid data foundations - from agent architectures and evaluation frameworks to production ML systems that drive measurable business outcomes. You will own problems end-to-end: identifying what to build, designing intelligent systems, measuring whether they work, and iterating based on what you learn. Your business acumen allows you to translate complex analytical approaches into actionable insights and stakeholder-friendly narratives, strengthening partnership and adoption across the enterprise.

Key Responsibilities

• 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
• Deeply understand our users - how they work, where they struggle, what they need - and advocate for building the right things, not just building things right
• Define success criteria for the intelligent systems you ship, measure whether they're working for users, and iterate until they are
• Design, build, and evaluate LLM-powered applications - agents, RAG systems, text-to-SQL, recommendation engines - owning the full lifecycle from prototype to production
• Establish feedback loops for intelligent systems: instrument, measure outcomes, learn what's working, and continuously improve
• Develop Python backend services and APIs that connect AI capabilities with modern web applications
• Build and maintain the data infrastructure (Snowflake, dbt, Airflow) that powers our AI products
• Effectively articulate complex technical concepts to non-technical partners, bridging gaps between technical teams and business operations
• Leverage AI-assisted development workflows (Claude Code, Cursor, or similar) to accelerate delivery and code quality
• Stay abreast of the latest advancements in LLMs, agent architectures, evaluation frameworks, and AI-assisted development

What We are Looking For

Education & Experience

• 3+ years' experience in Data Science, Machine Learning, or a related field
• BA/BS in Computer Science, Data Science, or related discipline (advanced degree is highly preferred)

Business Acumen & User Focus

• Experience owning business outcomes through intelligent systems - you've shipped an ML model, recommendation engine, or AI feature, established feedback loops, learned what's working, and continuously improved it based on user impact
• Opinionated about what to build next - you form a point of view grounded in user understanding and data, not just execute on a backlog
• User-focused: you talk to users, understand their workflows, and let that understanding drive your technical decisions
• Deep understanding of the "data - insights - action" workflow and how to measure whether your systems are driving outcomes
• Strong stakeholder engagement skills, with a track record of building trusted business partnerships

Technical Expertise

• 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
• Nice-to-have: Experience with AI-assisted development workflows (Claude Code, Cursor, Copilot, or similar)
• Nice-to-have: Experience with frontend technologies and UX design, particularly React

Communication & Collaboration

• Exceptional ability to simplify and communicate complex data science concepts to technical and non-technical audiences alike
• Experience working cross-functionally with engineers, analysts, and product leaders
• Steadfast commitment to continuous learning, collaboration, and fostering an inclusive, innovative team environment