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 responsible for helping Customer Experience teams to achieve their best, by intelligently solving repetitive work, so they can shift their focus to solving more sophisticated problems. We use the latest trends in Machine Learning and AI algorithms to help us on that mission, and we're passionate about empowering our customers.
As a Senior Staff Machine Learning Engineer you are a recognised 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 get to do every day
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 language/intent/sentiment analysis frameworks, conversational AI agents, and next-generation agent-assist 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.
Represent Zendesk externally—publishing papers, speaking at conferences, and engaging with the wider ML/AI community.
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 with agentic operation management, root cause diagnosis and proactive customer engagement and optimal routing.
How can we automate all customer service interactions as much as possible, from process automation to agent assistance and chatbots with a knowledge base?
How do we automate large-scale A/B testing and model evaluation (online and offline) to continually iterate and improve ML-driven triage and agent-assist tools?
What novel approaches or architectures (e.g., retrieval-augmented generation, 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 written in Python and Ruby.
Our servers live in AWS.
Our machine learning models rely on PyTorch.
Our ML pipelines use AWS Batch and MetaFlow.
Our data is stored in S3, RDS MySQL, Redis, ElasticSearch, Snowflake and Aurora.
Our services are deployed to Kubernetes using Docker, and use Kafka for stream-processing.
#LI-AO1
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.
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.
As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law.
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 [email protected] with your specific accommodation request.
Skills Required
- MSc degree in computer science, electrical engineering, math, or related areas
- Substantial track record of impactful research and deployment of ML/AI solutions
- Proven technical and research leadership across projects/teams
- Deep expertise in experimental design and statistical analysis
- Strong coding skills in Python and experience with ML frameworks
- Experience with large-scale experimentation and data analysis
- Outstanding mentorship and communication skills
- Recognized contributions to the scientific community
Zendesk Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zendesk and has not been reviewed or approved by Zendesk.
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Fair & Transparent Compensation — The company states a commitment to publishing base pay ranges and advancing pay equity, helping employees gauge fairness. Public messaging on pay equity and transparency signals structured, consistent compensation practices.
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Leave & Time Off Breadth — Time away programs include flexible PTO, dedicated well‑being days, emergency time off, and pregnancy loss leave. Parental leave is described as generous, and travel support exists for reproductive care where access is restricted.
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Healthcare Strength — Benefits language highlights comprehensive medical, dental/vision, mental health access, and an employee assistance program. These offerings are positioned as part of holistic wellbeing support across regions.
Zendesk Insights
What We Do
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. We advocate for digital first customer experiences— and we stick with it in our workplace. Over 5,000 employees worldwide are collaborating from kitchen tables, home offices, co-working spaces, and Zendesk workspaces to make one team.
Why Work With Us
We know one desk doesn’t fit all. At Zendesk, we prioritize remote work because we believe great work happens anywhere. Digital first is more than where we work though. We give our employees flexibility and choice in both where and how they work while also trusting them to be a team player.
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