Machine Learning Engineer, Sr.

Here’s the corrected LinkedIn-optimized version with the updated **San Francisco, CA remote listing location**, while preserving the actual eligibility requirement that candidates reside in the U.S. or Canada.## About the RoleThe Athletic Media Company is seeking a **Senior Machine Learning Operations Engineer** to help build, productionize, and maintain advanced machine learning systems that support highly visible product features. This role sits at the intersection of **machine learning, data engineering, infrastructure, and MLOps**, with a strong focus on reliable production ML systems.As the first Machine Learning Operations Engineer on the company's small data science team, you will play a critical role in establishing and improving **ML Ops practices, machine learning infrastructure, model deployment workflows, monitoring, and data pipelines**. You will work closely with data science and data engineering teams to streamline the machine learning lifecycle from training and validation through production deployment and monitoring.This is a **100% remote position** for candidates currently residing in the **United States or Canada**.## Key Responsibilities* Design, build, and maintain infrastructure for **machine learning model productionization**.* Develop reliable ML infrastructure supporting models used in highly visible product features.* Work closely with the data science team to streamline:* Model training* Model validation* Model deployment* Implement robust **monitoring and alerting** for:* Model performance* Model drift* Data quality* Help ensure machine learning models remain accurate and reliable in production.* Champion **MLOps best practices** across the data science organization.* Evaluate and integrate new technologies into the data science technology stack.* Help establish scalable and maintainable machine learning model pipelines and infrastructure.* Drive projects with minimal guidance and prioritize high-impact initiatives.* Build strong cross-functional relationships with data science and data engineering teams.* Explain sophisticated technical concepts to diverse audiences.* Use data to craft compelling technical and business stories.## Required Qualifications* **4–6 years of experience** as a Data Scientist, Data Engineer, Machine Learning Engineer, or related role.* Proven ability to build **machine learning model pipelines and infrastructure**.* Strong working knowledge of **Python**.* Strong working knowledge of **SQL** for pulling, transforming, and working with data.* Proven experience with machine learning frameworks such as:* Scikit-learn* PyTorch* Experience with cloud platforms such as:* Google Cloud Platform (GCP)* Amazon Web Services (AWS)* Microsoft Azure* Hands-on experience with:* Docker* Kubernetes* Apache Airflow* Ability to drive projects independently with minimal guidance.* Ability to prioritize high-impact work.* Strong verbal and written communication skills.* Ability to build effective cross-functional relationships.* Ability to explain sophisticated technical concepts to diverse audiences.* Ability to communicate insights and create compelling stories with data.## Technical Skills* Machine Learning Operations (MLOps)* Machine learning infrastructure* ML model productionization* Machine learning pipelines* Model training* Model validation* Model deployment* Model monitoring* Model performance monitoring* Model drift detection* Data quality monitoring* Python* SQL* Scikit-learn* PyTorch* GCP* AWS* Azure* Docker* Kubernetes* Apache Airflow* Data science infrastructure* Data engineering* Cloud infrastructure## Work Environment* **Employment Type:** Full-time* **Work Arrangement:** 100% Remote* **Listing Location:** San Francisco, CA, United States* **Eligible Candidate Locations:** United States or Canada* The role works closely with data science and data engineering teams.* As the first Machine Learning Operations Engineer on the data science team, this position will contribute significantly to the development of MLOps practices and machine learning infrastructure.## Compensation**Annual Base Salary Range: $140,000–$150,000 USD**Total compensation may vary based on factors including education, experience, skills, and location. Total compensation may also include non-cash rewards and benefits. The base salary range may be modified in the future.## BenefitsThe Athletic offers benefits and perks to full-time employees based on their country of residence.For U.S. employees, benefits include:* Employer-contributed medical, dental, and vision insurance plans.* Basic life and disability insurance.* Savings accounts for medical, wellness, and childcare expenses.* 401(k) retirement savings plan with employer match.* Paid time off.* Paid sick leave.* 12 paid holidays.* 15 days of accrued vacation to start.* Up to 20 weeks of paid parental leave.International employees receive global benefits packages with similar benefits and perks competitive with their local markets.## About The Athletic Media CompanyThe Athletic Media Company is building data-driven technology and digital experiences supported by advanced data science and machine learning capabilities. This role will help strengthen the company's machine learning infrastructure and enable data science teams to reliably deploy and operate production ML models.## Equal Employment OpportunityThe Athletic Media Company is an equal opportunity employer and encourages people from all backgrounds and experiences to apply. The company considers applicants without regard to protected characteristics under applicable law.Reasonable accommodations are available for qualified individuals throughout the application process and employment experience.