Senior ML Engineer

Job Description

At Zendesk, our focus is helping our customers build great relationships with their customers. Founded by three Danish entrepreneurs, Zendesk has experienced remarkable success and growth while maintaining a fun, positive, and down-to-earth culture.

We are looking for a Senior Machine Learning Engineer to join our Machine Learning team. You will be delivering AI / ML powered features for our customers at Zendesk scale.

What you’ll be doing

Work closely with ML Scientists to help bring ML-powered features into production

Contribute to discussions about technical design

Build tools to support model experimentation and model management

Collaborate with DevOps, feature teams, platform teams and product

Contribute to initiatives around improving the scalability and robustness of our platforms

Design, prototype, and refine scalable infrastructure

What you bring to the role

Required

Fluent in at least one of Python or Ruby

At least 5 years of background in building, scaling, and operating large scale applications

Previous experience delivering ML products, or in ML operations (MLOps)

Fluency with RESTful API, Kafka, Docker, Kubernetes, and cloud-like AWS or GCP

Ability to work with uncertainty and the flexibility to pivot with changing priorities

Deep respect and desire for team collaboration and members perspectives

Preferred

Experience with either Airflow or Metaflow

Experience with recent tooling around LLM evaluation and monitoring

Familiar with one of the machine learning libraries such as Pytorch

Experience with either SQL or DBT

Tech Stack

Our code is written in Python and Ruby

Our servers live in AWS

Our machine learning models rely on Pytorch

Our ML pipelines use Airflow and Metaflow

Our data is stored in S3, RDS MySQL and Snowflake

Our services and models are deployed to Kubernetes using Docker

Heavy usage of LLM technology from multiple providers

LI-AO1

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.