At a Glance
- Tasks: Develop AI-powered solutions and enhance our retrieval-augmented generation platform.
- Company: Join Zendesk, a leader in customer experience software with a global impact.
- Benefits: Flexible hours, professional development funds, and a remote-friendly environment.
- Why this job: Make a real difference for millions of customers using cutting-edge AI technology.
- Qualifications: 4+ years in machine learning, strong Python skills, and cloud service experience.
- Other info: Collaborative team culture with opportunities for growth and specialisation.
The predicted salary is between 36000 - 60000 ÂŁ per year.
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.
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?
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
- 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
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
- Flexible working hours
- Professional development funds
- Comfortable office and a remote‑friendly environment
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.
Zendesk is an equal opportunity employer, and we’re proud of our ongoing efforts to foster diversity & inclusion in the workplace.
Senior Machine Learning Engineer employer: Zendesk
Contact Detail:
Zendesk Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at Zendesk on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the Senior ML Engineer role.
✨Tip Number 2
Show off your skills in real-time! Consider participating in hackathons or coding challenges that focus on machine learning. This not only sharpens your skills but also gives you something impressive to talk about during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and cloud services knowledge. Practice explaining your thought process while solving problems, as communication is key in collaborative environments like Zendesk.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of the Zendesk team.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with machine learning systems and cloud services. We want to see how your skills align with the role, so don’t hold back on showcasing your relevant projects!
Show Off Your Communication Skills: Since excellent communication is key for this role, ensure your written application reflects clarity and professionalism. Use straightforward language and structure your thoughts well – it’ll make a great impression on us!
Highlight Your Collaborative Spirit: We love team players! Mention any experiences where you’ve worked closely with others, especially in mentoring or collaborative projects. This will show us that you’re not just a tech whiz but also someone who thrives in a team environment.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Zendesk
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, especially Python, AWS, and Kubernetes. Be ready to discuss how you've used these tools in your previous roles and how they relate to the challenges Zendesk is facing.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex machine learning problems in the past. Think about specific use cases where you optimised systems for speed and cost-efficiency, as this will resonate well with the team at Zendesk.
✨Emphasise Collaboration
Zendesk values teamwork, so be sure to highlight your experience working closely with product managers and other engineers. Share stories that demonstrate your ability to mentor others and foster a collaborative environment.
✨Ask Insightful Questions
Prepare thoughtful questions about Zendesk's RAG platform and its future direction. This shows your genuine interest in the role and helps you understand how you can contribute to their mission of improving customer experience.