### Who you are

4-6 years of experience as a data scientist, data engineer, or machine learning engineer with a proven ability to build machine learning model pipelines and infrastructure
Strong working knowledge of Python and SQL to pull, transform, and otherwise deal with data in all of its forms
Proven experience with ML frameworks (e.g., scikit-learn, PyTorch) and cloud platforms (e.g., GCP, AWS, Azure)
Hands-on experience with Docker, Kubernetes, and Airflow
Ability to drive projects with minimal guidance and prioritize high-impact work
Strong verbal and written communication skills with ability to build cross-functional relationships
Can explain sophisticated concepts to diverse audiences and craft compelling stories with data

### What the job involves

We are looking for a senior machine learning operations engineer who understands data pipelines, infrastructure, and model monitoring
In this role, you will work closely with our data science and data engineering teams to help us productionize and maintain advanced machine learning models
As the first machine learning operations engineer on our small data science team, your work will be critical to both the data team at The Athletic and the company as a whole
Design, build, and maintain machine learning model productionization infrastructure. These models will drive very visible product features at The Athletic, and your infrastructure is key to their success
Work with the rest of the data science team to streamline model training, validation, and deployment
Implement robust monitoring and alerting for model performance, drift, and data quality, ensuring our models remain accurate in production
Cultivate an outstanding data science environment by championing best practices in ML Ops and evaluating and integrating new technologies into our data science stack

### Benefits

Senior Machine Learning Operations Engineer

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