Senior Machine Learning Engineer - Copilot

Senior Machine Learning Engineer - Copilot

Zendesk

Lisbon, Portugal

As a Senior ML Engineer, you’ll be responsible for developing products in collaboration with our Research Scientists and other Machine Learning Engineers, and delivering high-quality ML and AI products to our customers, at a scale that most companies only dream of.

What you get to do every day

• Write robust, maintainable, and production-grade code to deliver ML-powered features (e.g., intent detection, sentiment/language analysis, intelligent agent routing) that directly impact millions of end users;
• Design, build, and optimize scalable, reliable ML pipelines for processing large volumes of structured and unstructured text data (including real-time customer conversations);
• Collaborate with ML Scientists and Product teams to productionize new models, LLM-powered services, and experiment with emerging AI technologies in the context of intelligent triage;
• Lead and participate in technical design, code reviews, and architecture decisions for ML/AI systems;
• Develop and evolve MLOps processes (CI/CD, model versioning, monitoring, and observability), ensuring efficient model deployment and high system reliability;
• Mentor and support junior engineers; share knowledge of model development, deployment, and best practices;
• Investigate and resolve complex production issues, including model failures, data drift, and system performance bottlenecks.

What you bring to the role

• Proven track record as a solid software engineer with a focus on Python-based software development;
• Advanced proficiency with scalable data processing frameworks and tools (e.g., Spark, AWS Batch, Airflow);
• Solid grasp of SQL, distributed database technologies, and data modeling for large/heterogeneous datasets;
• Experience with MLOps: CI/CD for ML, monitoring, model registries, automated retraining, and rollback;
• Familiarity with cloud environments (AWS preferred, but GCP/Azure experience valued), and microservices architectures (Kubernetes, Docker);
• Experience with modern NLP/LLM libraries and platforms (HuggingFace, OpenAI, etc.) and integrating LLMs into production workflows is a significant plus;
• A self-managed and dedicated approach with the ability to work independently;
• Strong problem-solving capabilities as well as the flexibility (of working style) to deal with changing and conflicting priorities;
• Knowledge of Machine Learning to keep up with the latest developments in the team and be part of all stages of the ML model development cycle;
• Ability to mentor, review code, and drive technical excellence within a multi-disciplinary team.