Job Description
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.
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.
What you’ll be doing:
* 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.
* Pioneer large, complex initiatives across product lines, such as building multilingual, real-time, conversational AI agents, and next-generation automated resolution solutions.
* Define and drive experimentation standards, statistically robust offline/online evaluations, and model governance for compliance, fairness, and explainability.
* Bridge cutting-edge research and production, collaborating with Engineering to build systems that scale globally and meet real-world performance constraints.
* Mentor, guide, and develop Senior Scientists and Engineers, fostering a culture of scientific rigor, creativity, and technical excellence across the organization.
* Advise leadership on ML/AI technology strategy and assess emerging industry trends for integration into Zendesk solutions.
* Mentor junior scientists and help grow the ML research culture.
Key challenges / use cases:
* 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?
* How can we automate all customer service interactions as much as possible with omni-channel bots with a knowledge base?
* How do we automate large-scale A/B testing and model evaluation (online and offline) to continually iterate and improve our RAG tools?
* 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?
* 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?
* How do we combine signals from conversation context, customer history, and external data to improve prediction and decision accuracy across our ML services?
* 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?
* 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?
* And many more!
What you bring to the role:
* MSc degree (PhD preferred) in computer science, electrical engineering, math, or related areas.
* Substantial track record of impactful research and deployment of ML/AI solutions at scale—preferably in NLP, LLMs or information retrieval.
* Proven technical and research leadership across projects/teams; ability to define research vision and influence organizational direction.
* Deep expertise in experimental design, statistical analysis, and ML science best practices.
* Strong coding skills in Python; experience with ML frameworks (preferably PyTorch).
* Experience with large-scale experimentation (e.g., A/B testing), data analysis, and performance tracking.
* Outstanding mentorship and communication skills—able to both advance scientific discourse and influence engineering/product execution.
* Be pragmatic and results oriented.
* Recognized contributions to the scientific community (publications, open source, talks) a strong plus.
What our tech stack looks like:
* Our code is largely written in Python, with some parts in Ruby
* Our platform is built on AWS
* Our machine learning models rely on PyTorch
* Our ML pipelines use AWS Batch and MetaFlow
* 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
...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
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 to learn more about how we engage with, and provide support to, our local communities.