Senior ML Scientist Amadora

Senior ML Scientist

Amadora, Lisboa, Portugal

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, among others) make their billions 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 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 Machine Learning Scientist, you will drive development, evaluation, and deployment of novel ML/AI models to power intelligent automation and customer service solutions at scale. You will collaborate closely with engineers, product managers, and functional teams to translate research into solutions directly impacting millions of support interactions.

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 (offline/online, A/B) to improve model accuracy and robustness.
• Work closely with ML Engineers to productionize ML models, 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

• Enrich customer service conversations with accurate language detection, intent recognition, and sentiment analysis to enable proactive customer engagement and optimal routing.
• Automate customer service interactions, from process automation to agent assistance and chatbots with a knowledge base.
• Optimize routing by matching tickets or chats to the most appropriate agent/team in real time across multiple languages and regions.
• Automate scalable A/B testing and model evaluation (online and offline) to continually iterate and improve ML-driven triage and assist tools.
• Develop novel approaches or architectures (augmented generation,
  - shot/fine-tuning) to extend conversational AI platforms for new customer support use cases and modalities.
• Operationalize, monitor, and update large language and ML models in dynamic production settings, ensuring model health, drift detection, and continuous learning.
• Combine signals from conversation context, customer history, and external data to improve prediction and decision accuracy across ML services.
• Incorporate emerging advancements in ML/AI research (large language models, efficient adaptation, ranking, retrieval, explainable AI) into Zendesk’s customer experience ecosystem.
• Bridge the gap between edge research and impactful product features, rapidly validating ideas in production and quantifying business value.

What you bring to the role

• MSc (or Ph
  D preferred) degree in computer science, electrical engineering, mathematics, or 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; 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 written in Python and Ruby.
• Servers hosted in AWS.
• ML models rely on Py
  Torch.
• ML pipelines use AWS Batch and Metaflow.
• Data stored in S3, RDS My
  SQL, Redis, Elasticsearch, Snowflake, and Aurora.
• Services deployed to Kubernetes with Docker and use Kafka for processing.

Hybrid work

In this role, 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. Attendance at the local office for part of the week is required; the specific schedule will be determined by the hiring manager.

The intelligent heart of customer experience

Zendesk software is built to bring calm to the chaotic world of customer service. We power billions of conversations with brands you know and love.

Equal opportunity statement

Zendesk is an equal‑opportunity employer and is dedicated to fostering global diversity, equity, and inclusion. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, sexual orientation, marital status, medical condition, or any other characteristic protected by law. If you are based in the United States and want more information about your EEO rights, click here. We make reasonable accommodations for applicants with disabilities; if you need assistance, email peopleandplaces@zendesk.com.