The Role
The Senior Machine Learning Operations Engineer will design, build, and maintain ML infrastructure, streamline model deployment, and monitor performance to ensure the success of machine learning models at The Athletic.
Summary Generated by Built In
About Us
Powered by one of the largest global newsrooms in sports media, The Athletic brings sports fans the most comprehensive stories about the teams, sports and athletes they love. The Athletic’s newsroom of 500+ full-time staff delivers in-depth coverage of hundreds of professional and college teams across more than 47 North American markets and all 20 football clubs in the English Premier League, as well as many Championship clubs.
About the Role
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.
This role is 100% remote for candidates currently residing in either the United States or Canada.
Responsibilities
- 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.
Requirements
- 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.
The annual base salary range for this role is $140,000.00 - $150,000.00 USD. The total compensation offered for this position may vary based on factors such as education, experience, skills, and location.
For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock. Benefits may include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs.
For roles outside of the U.S., information on benefits will be provided during the interview process.
We are excited to learn more about you and your experience. To keep our hiring process as fair and authentic as possible, we ask that you submit your own work and not use GenAI tools to generate substantive content during the application and interview process. If you are a candidate for a technical role, we will let you know what specific tools you are permitted to use for your technical assessment.
The Athletic Media Company is an equal opportunity employer and enthusiastically encourages people from all backgrounds and experiences to apply. The Athletic will consider all applicants without regard to race, religion, color, national origin, ancestry, physical and/or mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, transgender status, age, sexual orientation, military or veteran status, or any other protected characteristic under applicable law.
Click here to review our Applicant Privacy Notice, which describes how and when The Athletic Media Company collects, uses, and shares certain personal information of job applicants and prospective employees.
Beware of fraudulent job recruiting schemes! Our recruiters use [email protected] exclusively, and our team members will use an email address with @theathletic.com domain. We do not conduct interviews via text or instant message and we do not ask candidates to download software, to purchase equipment through us, or to provide sensitive personally identifiable information, such as bank accounts or social security numbers. If you have been contacted by someone claiming to be a member of the recruiting/HR team at The Athletic but operating from a different email address about a job offer, please report it as potential job fraud to the law enforcement and to [email protected].
Skills Required
- 4-6 years of experience as a data scientist, data engineer, or machine learning engineer
- Strong working knowledge of Python and SQL
- Proven experience with ML frameworks (e.g., scikit-learn, PyTorch)
- Experience with cloud platforms (e.g., GCP, AWS, Azure)
- Hands-on experience with Docker, Kubernetes, and Airflow
- Strong verbal and written communication skills
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The Company
What We Do
Here for every sports story that matters. -- The Athletic (http://theathletic.com) is a subscription-based media publisher of smarter sports coverage for die-hard fans. Founded in 2016, The Athletic’s all-star team of writers have produced thousands of quality stories for subscribers free of ads, pop-ups and auto-play videos. The Athletic now offers in-depth local coverage in 47 North American pro sports markets along with premium national coverage across MLB, NFL, NBA, NHL, NCAA & more. Readers can count on original, authentic storytelling written by talented local and national sports journalists like Ken Rosenthal, Pierre LeBrun, Seth Davis, Stewart Mandel, Shams Charania and many more. The company is headquartered in San Francisco, CA.
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