At a Glance
- Tasks: Lead the design and deployment of innovative ML models for customer service.
- Company: Join Zendesk, a leader in enhancing customer experiences globally.
- Benefits: Flexible hours, professional development funds, and a supportive work environment.
- Why this job: Make a real impact on millions of customers with cutting-edge AI technology.
- Qualifications: MSc or PhD in relevant fields and strong experience in ML/AI solutions.
- Other info: Collaborative culture with opportunities for mentorship and career growth.
The predicted salary is between 43200 - 72000 £ per year.
Overview
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 Software and ML Engineers, 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.
As a Staff Machine Learning Scientist you are a recognized leader and domain expert, responsible for advancing the state-of-the-art in ML/AI for customer service at a global scale. You steer research vision, mentor scientists across teams, and drive adoption of foundational models powering Zendesk’s most impactful features.
Responsibilities
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Lead end-to-end design, development, and deployment of novel ML/LLM models and algorithms—defining research agendas that shape Zendesk’s AI-powered roadmap.
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Pioneer large, complex initiatives across product lines, such as building multilingual, real-time, conversational AI agents, and next-generation automated resolution solutions.
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Define and drive experimentation standards, statistically robust offline/online evaluations, and model governance for compliance, fairness, and explainability.
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Bridge cutting-edge research and production, collaborating with Engineering to build systems that scale globally and meet real-world performance constraints.
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Mentor, guide, and develop Senior Scientists and Engineers, fostering a culture of scientific rigor, creativity, and technical excellence across the organization.
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Advise leadership on ML/AI technology strategy and assess emerging industry trends for integration into Zendesk solutions.
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Mentor junior scientists and help grow the ML research culture.
Key challenges / use cases
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How do we enrich customer service conversations with accurate language detection and task classification, efficient retrieval and real-time conversation generation, to enable proactive customer engagement and optimal resolution?
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How can we automate all customer service interactions as much as possible with omni-channel bots with a knowledge base?
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How do we automate large-scale A/B testing and model evaluation (online and offline) to continually iterate and improve our RAG tools?
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What novel approaches or architectures (e.g., retrieval-augmented generation, agentic, few-shot/fine-tuning strategies) can extend our conversational AI platforms to unlock new customer support use cases and modalities?
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How do we efficiently operationalize, monitor, and update large-scale (LLM/ML) models in dynamic, high-throughput production settings, ensuring model health, drift detection, and continuous learning?
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How do we combine signals from conversation context, customer history, and external data to improve prediction and decision accuracy across our ML services?
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What are the emerging advancements in ML/AI research (e.g., large language models, efficient adaptation, re-ranking, retrieval, or explainable AI) that should be incorporated into Zendesk’s customer experience ecosystem?
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How can we bridge the gap between cutting-edge research and impactful product features, rapidly validating ideas in production and quantifying their real-world business value?
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And many more!
What you bring to the role
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MSc degree (PhD preferred) in computer science, electrical engineering, math, or related areas.
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Substantial track record of impactful research and deployment of ML/AI solutions at scale—preferably in NLP, LLMs or information retrieval.
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Proven technical and research leadership across projects/teams; ability to define research vision and influence organizational direction.
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Deep expertise in experimental design, statistical analysis, and ML science best practices.
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Strong coding skills in Python; experience with ML frameworks (preferably PyTorch).
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Experience with large-scale experimentation (e.g., A/B testing), data analysis, and performance tracking.
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Outstanding mentorship and communication skills—able to both advance scientific discourse and influence engineering/product execution.
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Be pragmatic and results oriented.
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Recognized contributions to the scientific community (publications, open source, talks) a strong plus.
What our tech stack looks like
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Our code is largely written in Python, with some parts in Ruby
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Our platform is built on AWS
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Our machine learning models rely on PyTorch
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Our ML pipelines use AWS Batch and MetaFlow
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Data is stored in RDS MySQL, Redis, S3, ElasticSearch, Kafka, and Athena
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Services are deployed to Kubernetes using Docker, with Kafka for stream processing
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Infrastructure health is monitored using Datadog and Sentry
What we offer
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Team of passionate people who love what they do!
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Exciting opportunity to work with LLMs and RAG (retrieval augmented generation), rapidly evolving fields in AI
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Ownership of the product features at scale, making a significant impact for millions of customers
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Opportunity to learn and grow!
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Possibility to specialise in areas such as security, performance, and reliability
…and everything you need to be effective and maintain work-life balance
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Flexible working hours
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Professional development funds
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Comfortable office and a remote-friendly environment
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.
Zendesk is an equal opportunity employer, and we’re proud of our ongoing efforts to foster diversity & inclusion in the workplace. Individuals seeking employment at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, physical or mental disability, military or veteran status, or any other characteristic protected by applicable law.
By submitting your application, you agree that Zendesk may collect your personal data for recruiting, global organization planning, and related purposes. Zendesk\’s Candidate Privacy Notice explains what personal information Zendesk may process, where Zendesk may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Zendesk’s use of your personal information.
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Hybrid: In this role, our hybrid experience is designed at the team level to give you a rich onsite experience packed with connection, collaboration, learning, and celebration – while also giving you flexibility to work remotely for part of the week. This role must attend our local office for part of the week. The specific in-office schedule is to be determined by the hiring manager.
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.
Zendesk is an equal opportunity employer, and we’re proud of our ongoing efforts to foster global diversity, equity, & inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. We are an AA/EEO/Veterans/Disabled employer. If you are based in the United States and would like more information about your EEO rights under the law, please click here.
Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to peopleandplaces@zendesk.com with your specific accommodation request.
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Staff Machine Learning Scientist employer: Zendesk
Contact Detail:
Zendesk Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Machine Learning Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current Zendesk employees on LinkedIn. A friendly chat can sometimes lead to opportunities that aren’t even advertised!
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or GitHub with projects related to machine learning or AI, make sure to highlight them during interviews. It’s a great way to demonstrate your expertise and passion.
✨Tip Number 3
Prepare for those technical interviews! Brush up on your coding skills, especially in Python and ML frameworks like PyTorch. Practice common algorithms and be ready to discuss your past projects in detail.
✨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 joining the Zendesk team!
We think you need these skills to ace Staff Machine Learning Scientist
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for machine learning and AI shine through! We want to see how your passion aligns with our mission to enhance customer experience using cutting-edge technology.
Tailor Your Experience: Make sure to highlight your relevant experience in ML/AI, especially in NLP or LLMs. We love seeing how your past projects can contribute to our goals, so don’t hold back on the details!
Be Clear and Concise: While we appreciate creativity, clarity is key! Keep your application straightforward and to the point, ensuring that your skills and experiences are easy to understand at a glance.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Zendesk
✨Know Your ML Stuff
Make sure you brush up on the latest trends in machine learning, especially around NLP and LLMs. Be ready to discuss your past projects and how they relate to Zendesk's goals. Show them you’re not just a techie but someone who understands the bigger picture of customer experience.
✨Prepare for Technical Questions
Expect some deep dives into your coding skills, particularly in Python and frameworks like PyTorch. Practice explaining your thought process while solving problems, as this will demonstrate your technical prowess and ability to communicate complex ideas clearly.
✨Show Your Leadership Skills
As a Staff Machine Learning Scientist, you'll be expected to mentor others. Prepare examples of how you've led teams or projects in the past. Highlight your ability to influence and guide others, as well as your experience in fostering a culture of scientific rigor.
✨Think About Real-World Applications
Zendesk is all about improving customer experience, so come with ideas on how to apply ML/AI solutions in practical scenarios. Think about how you can bridge research and production, and be ready to discuss how your innovations can impact their products and customers.