Senior Machine Learning Engineer

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 developing intelligent products that make agents more productive by automating manual work. From exploration and design to production deployment and maintenance. We are here to maximize agent productivity through tools and experiences that enable agents to easily accomplish their tasks so that they can provide better, faster customer support.

We are looking for a Senior Machine Learning Engineer to build the ML platform which provides robust infrastructure to transform models into products for our 145,000+ customers. The ideal candidate will have experience as a software engineer or MLOps engineer, a desire to work in ML/AI domain and a deep interest in developing complex systems and automating the simple ones.

What you’ll be doing

• Build software to move machine learning from experiment to production
• Work closely with Data Science, ML Engineers and Product teams to build ML-powered features and to increase ML adoption across Zendesk
• Actively contribute to discussions about technical designs and standards.
• Champion initiatives to improve the scalability and robustness of our platforms
• Design, prototype, and refine scalable infrastructure
• Build really cool products with a great team

What you bring to the role

• At least 4 years building scalable and stable software applications
• Proficiency in at least one of our core languages: Python or Java or Ruby 
• Experience with AWS infrastructure
• Experience or knowledge of Docker and Kubernetes
• 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.

Preferred Qualifications

• Experience building and deploying machine learning models. Understanding of end-to-end machine learning pipelines and components.
• Familiarity with data engineering tools e.g. Spark
• Familiarity with AI/ML workflows and associated tooling e.g. Sagemaker, ML Flow, Metaflow

Tech Stack

• Our code is written in Python, Java
• Our servers live in AWS
• Our data is stored in S3, RDS MySQL, Redis, ElasticSearch, and Aurora and streamed through Kafka
• Our services are deployed to Kubernetes using Docker

What we offer

• Ownership of the product features implementation you work on
• What you will be doing will have a huge impact
• Team of passionate people who love what they do!
• Exciting features, ability to implement your own ideas and improvements
• Opportunity to learn and grow!
• Possibility to specialise in areas like 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 setup
• ​Internet and Phone bill allowance
• Premium Medical Insurance as well as Private Life Assurance