.By clicking "Apply Now," I understand and agree that Zendesk and its affiliates will collect and process my information in accordance with Zendesk's Candidate Privacy Notice. 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 developing tools and infrastructure needed through all phases of the ML model life cycle. From exploration and design to production deployment and maintenance. We are here to support ML teams in 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 are looking for a Staff 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 platform 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 Basic Qualifications: At least 6 years building scalable and stable software applications Proficiency in at least one of our core languages: Python 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. Experience or knowledge of Infrastructure as Code tools (e.G. Terraform) Experience building and deploying machine learning models. Strong 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, Scala and Go Our servers live in AWS Our team manages infrastructure using AWS CloudFormation, Terraform Our data is stored in S3, RDS MySQL, Redis, ElasticSearch, and Aurora and streamed through Kafka Our services are deployed to Kubernetes using Docker 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
