Senior Machine Learning Engineer

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.

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 ML Engineer, you'll be responsible for developing products in collaboration with our Research Scientists and other Machine Learning Engineers, and delivering high-quality ML and AI products to our customers, at a scale that most companies only dream of.

What you get to do every day

• Write robust, maintainable, and production-grade code to deliver ML-powered features (e.g., intent detection, sentiment/language analysis, intelligent agent routing) that directly impact millions of end users.
• Design, build, and optimize scalable, reliable ML pipelines for processing large volumes of structured and unstructured text data (including real-time customer conversations).
• Collaborate with ML Scientists and Product teams to productionize new models, LLM-powered services, and experiment with emerging AI technologies in the context of intelligent triage.
• Lead and participate in technical design, code reviews, and architecture decisions for ML/AI systems.
• Develop and evolve MLOps processes (CI/CD, model versioning, monitoring, and observability), ensuring efficient model deployment and high system reliability.
• Mentor and support junior engineers; share knowledge of model development, deployment, and best practices.
• Investigate and resolve complex production issues, including model failures, data drift, and system performance bottlenecks.

Key challenges / use cases

• How do we enrich customer service conversations with accurate language detection, intent recognition, and real-time sentiment analysis, to enable 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 optimize routing at scale—matching tickets or chats to the most appropriate agent/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 agent-assist tools?
• How do we extend our retrieval and information extraction platforms to support new conversational AI use cases?
• How do we efficiently serve and monitor large ML/LLM models in a high-throughput, low-latency production environment?
• How do we combine signals from conversation context, customer history, and external data to improve prediction and decision accuracy across our ML services?
• How do we ensure fairness, explainability, and compliance in ML-driven customer interactions?
• And many more

What You Bring To The Role

• Proven track record as a solid software engineer with a focus on Python-based software development.
• Advanced proficiency with scalable data processing frameworks and tools (e.g., Spark, AWS Batch, Airflow).
• Solid grasp of SQL, distributed database technologies, and data modeling for large/heterogeneous datasets.
• Experience with MLOps: CI/CD for ML, monitoring, model registries, automated retraining, and rollback.
• Familiarity with cloud environments (AWS preferred, but GCP/Azure experience valued), and microservices architectures (Kubernetes, Docker).
• Experience with modern NLP/LLM libraries and platforms (HuggingFace, OpenAI, etc.) and integrating LLMs into production workflows is a significant plus.
• A self-managed and dedicated approach with the ability to work independently.
• Strong problem-solving capabilities as well as the flexibility (of working style) to deal with changing and conflicting priorities.
• Knowledge of Machine Learning to keep up with the latest developments in the team and be part of all stages of the ML model development cycle..
• Ability to mentor, review code, and drive technical excellence within a multi-disciplinary team.

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.

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.

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 with your specific accommodation request.