About Zendesk
Zendesk’s people have one goal in mind: to make Customer Experience better. Our products help more than 125,000 global brands (AirBnb, Uber, JetBrains, Slack, among others) make their billions of customers happy, every day.
Our team is dedicated to providing a state-of-the-art retrieval-augmented generation (RAG) platform across multiple channels; including customer service bots, email and search. In collaboration with ML 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 quickly find answers to their questions, and helping our customers make the most of their knowledge base.
We’re looking for a Senior ML engineer to join our team and play a key role in levelling up the RAG platform powering Zendesk!
What you’ll be doing
- Delivering AI-powered capabilities to our customers at Zendesk scale using the latest in LLM technology
- Working closely with Product Management, ML Scientists and other ML Engineers to define feature scope and implementation strategies
- 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
- Contributing to discussions regarding technical design and best practices
- Writing clean and maintainable code to meet the team’s delivery commitments
Here some of the challenges you will be working on:
- How do we best expand our RAG platform to handle new use cases?
- How do we optimize our system for both speed and cost-efficiency?
- How do we incorporate multiple sources of context to improve the accuracy of our generated answers?
- How do we make the best use of rapidly evolving LLM technologies?
- And many more!
About Zendesk
Zendesk builds software for better customer relationships. It empowers organizations to improve customer engagement and better understand their customers. Zendesk products are easy to use and implement. They give organizations the flexibility to move quickly, focus on innovation, and scale with their growth. More than 100,000 paid customer accounts in over 150 countries and territories use Zendesk products. Based in San Francisco, Zendesk has operations in the United States, Europe, Asia, Australia, and South America.
Interested in knowing what we do in the community? Check out the Zendesk Neighbor Foundation to learn more about how we engage with, and provide support to, our local communities.
The intelligent heart of customer experience
Zendesk software was designed 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 with LLMs and RAG (retrieval augmented generation), rapidly evolving fields in AI
- 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
...and everything you need to be effective and maintain work-life balance
- Flexible working hours
- Professional development funds
- Comfortable office and a remote-friendly environment
What you bring to the role
Basic Qualifications
- 4+ years developing machine learning systems in Python
- Solid understanding of architecture and software design patterns for server-side applications
- Experience with managing and deploying cloud services with a cloud provider (AWS, GCP, Azure)
- Experience building scalable and stable software applications
- Collaborative and growth mindset, with a commitment to ongoing learning and development
- Self-managed and agile, with the ability to problem-solve independently
- Excellent communication skills, both written and verbal
Preferred Qualifications
- Experience with using LLMs at scale
- Experience in designing and implementing RAG systems
- Experience with managing and deploying cloud services with AWS
- Proven experience making data-driven engineering decisions; formulating hypotheses, conducting experiments, and analyzing results.
What our tech stack looks like
- Our code is largely written in Python, with some parts in Ruby
- Our platform is built on AWS
- Data is stored in RDS MySQL, Redis, S3, ElasticSearch, Kafka, and Athena
- Services are deployed to Kubernetes using Docker, with Kafka for stream processing
- Infrastructure health is monitored using Datadog and Sentry
