Staff Machine Learning Engineer

Staff Machine Learning Engineer

Zendesk

Remote

We’re looking for a Staff Machine Learning Engineer to join our team and play a key role in leveling up the search platform powering Zendesk!

What you’ll be doing

• Delivering AI-powered capabilities to our customers at Zendesk scale using latest LLM technologies
• Working closely with Product Management, ML Scientists and fellow Engineers both within the team and across the company to define feature scope and implementation strategies, using ML technology
• Mentoring junior team members, as well as pairing with more experienced colleagues to foster mutual learning
• Supporting our deployed services to ensure a high level of stability and reliability
• Writing clean and maintainable code to meet the team’s delivery commitments
• Contributing to discussions regarding technical design and best practices
• Here some of the challenges you will be working on:
  • How do we expand our RAG platform to handle new use cases?
  • How do we integrate and improve hybrid search solutions combining vector embeddings and keyword-base retrieval?
  • How do we enhance the ranking of search results?
  • How do we optimize our indexing pipeline for speed and cost-efficiency?
  • How do we best provide a retrieval platform across multiple channels?
  • How do we make the best use of rapidly evolving LLM technologies?
  • And many more!

What you bring to the role

Basic Qualifications:

• Proficiency in programming languages such as Python or Ruby, along with experience in relevant testing frameworks
• Solid understanding of architecture and software design patterns for server-side and web applications
• Collaborative and growth mindset, with a commitment to ongoing learning and development
• Self-managed, dedicated approach with the ability to work independently
• Experience building scalable and stable software applications
• Ability to formulate hypotheses, conduct experiments, and analyze results to inform engineering decisions

Preferred Qualifications:

• Experience in designing, implementing, and optimizing search solutions, ideally leveraging Machine Learning techniques and Elasticsearch to enhance search relevance and performance
• Experience with managing and deploying cloud services with AWS
• Experience with event-driven, distributed architecture using Kafka