Job Description
Zendesk’s people have one goal in mind: to make Customer Experience better. Our products help more than 145,000 global brands (AirBnb, Uber, JetBrains, Slack, among others) make their billions of customers happy, every day.
Our team is dedicated to providing a robust full-text search experience for our customers across multiple channels; including help centers and agentic RAG (retrieval-augmented-generation) bots. In collaboration with ML engineers and scientists, we deliver high-quality AI products leveraging the latest tools and techniques, and serve them at a scale that most companies can only dream of. We’re passionate about empowering end-users to find what they’re looking for, and helping our customers get the most out of their knowledge base.
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!
The intelligent heart of customer experience
Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love.
Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.
What we offer
- Team of passionate people who love what they do!
- Exciting opportunity to work on RAG (retrieval-augmented-generation), a rapidly evolving field in AI and natural language processing
- Ownership of the product features at scale, making a significant impact for millions of customers
- Opportunity to learn and grow!
- Possibility to specialise in areas such as security, performance, and reliability
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
Tech Stack
- Our codebase is primarily written in Python and Ruby
- Our machine learning models rely on PyTorch
- Our platform is built on AWS
- Data is stored in RDS MySQL, Redis, S3, ElasticSearch, Kafka, and Snowflake
- Services are deployed on Kubernetes using Docker, Kafka is used for stream processing
- Infrastructure health is monitored using Datadog and Sentry
