Senior Machine Learning Operations Engineer (MLOps)

TL;DR

Senior Machine Learning Operations Engineer (MLOps): Design, build, and maintain machine learning model productionization infrastructure with an accent on data pipelines, model monitoring, and deployment. Focus on streamlining model training and validation, implementing robust alerting for performance, drift, and data quality, and championing best practices in ML Ops.

Location: 100% remote for candidates currently residing in the United States or Canada

Salary: $140,000 - $150,000 USD

Company

Powered by one of the largest global newsrooms in sports media, delivering in-depth coverage of professional and college teams across North America and the English Premier League.

What you will do

• Design, build, and maintain ML model productionization infrastructure for visible product features.
• Streamline model training, validation, and deployment with data science and engineering teams.
• Implement monitoring and alerting for model performance, drift, and data quality.
• Champion ML Ops best practices and integrate new technologies into the data science stack.

Requirements

• 4-6 years experience as data scientist, data engineer, or ML engineer building model pipelines and infrastructure
• Strong Python and SQL for data handling
• Experience with ML frameworks (scikit-learn, PyTorch) and cloud platforms (GCP, AWS, Azure)
• Hands-on with Docker, Kubernetes, and Airflow
• Ability to drive projects independently and communicate complex concepts effectively

Culture & Benefits

• Medical, dental, vision benefits, FSAs, company-matching 401(k)
• Paid vacation, sick days, parental leave
• Tuition reimbursement and professional development programs
• Potential variable pay including annual bonus and restricted stock (US roles)