Senior Machine Learning Operations Engineer, The Athletic

$140-150k

SQL

AWS

Docker

Kubernetes

GCP

Python

Airflow

Azure

Scikit-Learn

PyTorch

Mid and Senior level

Remote from Canada, US

Subscription-based sports content publisher

Be an early applicant

Subscription-based sports content publisher

501-1000 employees

B2CPublishingContentSports

Be an early applicant

$140-150k

SQL

AWS

Docker

Kubernetes

GCP

Python

Airflow

Azure

Scikit-Learn

PyTorch

Mid and Senior level

Remote from Canada, US

501-1000 employees

B2CPublishingContentSports

Company mission

To produce smarter coverage for die-hard fans and redefine the way fans get access to sports content by flipping the normal model for sports journalism.

Job

Company

Role

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

Our take

The Athletic provides authentic, in-depth coverage written by journalists who know the teams they write about inside out. Its model bucks the trend of traditional sports journalism outfits by asking for a subscription rather than relying on ad-revenue.

Despite initial doubts that users would be willing to pay for sports journalistic content, The Athletic has found significant success and was acquired by the New York Times in 2022. Despite it operating at a loss directly after the takeover, it was clear that the New York Times perceived this as a long-term investment.

In 2025, it was reported that The Athletic was now profitable, which aligns well with its parent's prediction of profitability within 4 years. This has been aided by accelerated customer growth alongside the rising trend of subscription-based sports news.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Top investors

20% female employees

8% employee growth in 12 months

Glassdoor (3.9)

Trustpilot (1.1)

Company

Funding (last 2 of 7 rounds)

Jan 2020

$50m

SERIES D

May 2019

$21.8m

SERIES C

Total funding: $139.7m

Company benefits

Paid Time Off
Paid Sick Leave
Paid Parental Leave
401 (k)
Short & Long Term Disability
Free Subscription
Competitive Health Care
HSA & FSA
Commuter Benefits

Company HQ

Financial District, San Francisco, CA

Leadership

Adam Hansmann

(President & Co-Founder)

Previously a McKinsey Business Analyst and then Associate at Calera Capital.

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