Senior ML Scientist

Senior Machine Learning Scientist – Corroios, Setúbal, Portugal

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, Jet
Brains, Slack, and others—make their millions of customers happy every day.

Our team is responsible for helping Customer Experience teams achieve their best by intelligently solving repetitive work so they can focus on more sophisticated problems. We use the latest trends in Machine Learning and AI algorithms to advance that mission and passionately empower our customers.

What you get to do every day

• Research, prototype, and develop NLP/ML models for use cases such as intent detection, assist, chatbots, and intelligent agent routing.
• Design and execute rigorous experiments and evaluations—including offline/online, A/B testing—to improve model accuracy and robustness.
• Work closely with ML Engineers to productionize ML, including data pipelines, scalable model serving, and monitoring.
• Analyze large, multilingual customer interaction datasets to uncover insights and power new solutions.
• Participate in technical reviews and share knowledge of underlying ML methodologies and best practices.
• Present your work to a disciplinary, global audience.
• Stay up to date with recent literature in Machine Learning and Natural Language Processing (NLP) and share knowledge internally.
• Champion initiatives to improve the quality and robustness of Zendesk AI capabilities.
• 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, intent recognition, and time‑sentiment analysis to enable proactive 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 optimize routing—matching tickets or chats to the most appropriate agent or team—in real time across multiple languages and regions?
• How do we automate large‑scale A/B testing and model evaluation (online and offline) to continually iterate and improve ML‑driven triage and assist tools?
• What novel approaches or architectures (e. g. , 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 emerging advancements in ML/AI research—large language models, efficient adaptation, ranking, retrieval, or explainable AI—should be incorporated into Zendesk’s customer experience ecosystem?
• How can we bridge the gap between edge research and impactful product features, rapidly validating ideas in production and quantifying their business value?
• And many more!

What you bring to the role

• MSc degree (Ph. D. preferred) in computer science, electrical engineering, mathematics, or a related field.
• Deep knowledge of ML theory, algorithms, and modern NLP/LLM techniques.
• Demonstrated ability to conduct independent research and deliver high‑grade ML solutions.
• Strong coding skills in Python and experience with ML frameworks (preferably Py
  Torch).
• Experience with large‑scale experimentation (e. g. , A/B testing), data analysis, and performance tracking.
• Strong collaboration and communication abilities.
• Pragmatic, results‑oriented mindset.

What our tech stack looks like

• Code is written in Python and Ruby.
• Servers run on AWS.
• ML models rely on Py
  Torch.
• ML pipelines use AWS Batch and Meta
  Flow.
• Data is stored in S3, RDS My
  SQL, Redis, Elastic Search, Snowflake, and Aurora.
• Services are deployed to Kubernetes using Docker and use Kafka for processing.

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 providing flexibility to work remotely for part of the week. You must attend our local office for part of the week. The specific office schedule is to be determined by the hiring manager.

Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working enables purposeful collaboration in person at one of our many Zendesk offices worldwide, while giving flexibility for remote work during part of the week.

As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence 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 committed to fostering global diversity, equity, and inclusion in the workplace. Individuals seeking employment are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, sexual orientation, marital status, medical condition, ancestry, disability, military status, or veteran status. 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, please send an email to peopleandplaces@zendesk.com with your specific accommodation request.