Senior ML Engineer: RAG & Search at Scale (Remote)

Zendesk; Portugal; Híbrido; EUR 91 000 - 137 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

RAG AI focus

Hybrid work model

Mentorship

Growth opportunities

Resumo da oferta

Zendesk seeks a Staff Machine Learning Engineer to advance our full-text search platform that powers customer interactions worldwide. You will deliver AI-powered capabilities at scale, collaborating with product managers, ML scientists and engineers to define features and implementation strategies.

You’ll mentor teammates, maintain service stability, and write clean, scalable code in Python or Ruby, deploying on AWS with Elasticsearch, Kafka and Kubernetes, while improving performance and

Qualificações

• Proficiency in Python or Ruby and testing frameworks.
• Strong understanding of server-side architecture and design patterns.
• Collaborative and growth mindset with ability to work independently.
• Experience building scalable, reliable software systems.

Responsabilidades

• Deliver AI-powered capabilities at Zendesk scale using latest ML tech.
• Define feature scope and implementation strategies with PMs, ML scientists, and engineers.
• Mentor junior engineers and pair with experienced colleagues for knowledge transfer.
• Maintain reliability and stability of deployed services.
• Write clean, maintainable code and contribute to technical design discussions.
• Address challenges in expanding RAG platforms and improving search ranking and indexing pipelines.

Conhecimentos

Python

Ruby

Testing frameworks

Software design patterns

Collaboration

Independent work

Scalable software

Hypothesis testing

Ferramentas

Elasticsearch

AWS

Kafka

Kubernetes

Docker

PyTorch

MySQL

Redis

Descrição da oferta de emprego

Zendesk seeks a Staff Machine Learning Engineer to advance our full-text search platform that powers customer interactions worldwide. You will deliver AI-powered capabilities at scale, collaborating with product managers, ML scientists and engineers to define features and implementation strategies.

You’ll mentor teammates, maintain service stability, and write clean, scalable code in Python or Ruby, deploying on AWS with Elasticsearch, Kafka and Kubernetes, while improving performance and