Staff ML Engineer: Scale RAG & Search Platform

JobCubby; København; Hybrid; DKK 680,000 - 1,021,000; Full time

Benefits offered by this job

RAG projects

Ownership of features

Growth opportunities

Job summary

Zendesk seeks a Staff Machine Learning Engineer to elevate our full-text search platform and deliver AI-powered capabilities at scale. You will collaborate with Product Management, ML Scientists and Engineers to define features and implement solutions using latest ML tech.

Join a hybrid, globally distributed team. You will mentor juniors, ensure service stability, write clean code, and help shape best practices while exploring RAG, vector search, and retrieval architectures.

Qualifications

• Proficiency in Python or Ruby with testing frameworks.
• Understanding of server-side architecture and design patterns.
• Collaborative and growth mindset with ability to work independently.
• Experience building scalable, stable software applications.
• Ability to formulate hypotheses, run experiments, and analyze results.
• Experience designing/search solutions with ML and Elasticsearch.
• Experience deploying cloud services on AWS.
• Event-driven, distributed architecture using Kafka.

Responsibilities

• Delivering AI-powered capabilities to customers at Zendesk scale using latest LLM technologies.
• Collaborate with Product Management, ML Scientists and Engineers to define feature scope.
• Mentor junior teammates and pair with experienced colleagues.
• Maintain deployed services for high stability and reliability.
• Write clean, maintainable code meeting delivery commitments.
• Contribute to technical design discussions and best practices.

Skills

Python

Ruby

Testing frameworks

Server-side architecture

Independent work

Collaboration

Scalable software

Experimentation

Tools

Elasticsearch

AWS

Kafka

Kubernetes

Docker

PyTorch

Snowflake

Job description

Zendesk seeks a Staff Machine Learning Engineer to elevate our full-text search platform and deliver AI-powered capabilities at scale. You will collaborate with Product Management, ML Scientists and Engineers to define features and implement solutions using latest ML tech.

Join a hybrid, globally distributed team. You will mentor juniors, ensure service stability, write clean code, and help shape best practices while exploring RAG, vector search, and retrieval architectures.