Senior Machine Learning Engineer

About SiriusXM

SiriusXM and its brands (Pandora, SiriusXM Media, AdsWizz, Simplecast, and SiriusXM Connect) are leading a new era of audio entertainment and services by delivering the most compelling subscription and ad-supported audio entertainment experience for listeners — in the car, at home, and anywhere on the go with connected devices. Our vision is to shape the future of audio, where everyone can be effortlessly connected to the voices, stories and music they love wherever they are.

This is the place where a diverse group of emerging talent and legends alike come to share authentic and purposeful songs, stories, sounds and insights through some of the best programming and technology in the world. Our critically-acclaimed, industry-leading audio entertainment encompasses music, sports, comedy, news, talk, live events, and podcasting.

SiriusXM is the leading audio entertainment company in North America, and the premier programmer and platform for subscription and digital advertising-supported audio products. SiriusXM's platforms collectively reach approximately 150 million listeners, the largest digital audio audience across paid and free tiers in North America, and deliver music, sports, talk, news, comedy, entertainment and podcasts. Pandora, a subsidiary of SiriusXM, is the largest ad-supported audio entertainment streaming service in the U.S. SiriusXM's subsidiaries Simplecast and AdsWizz make it a leader in podcast hosting, production, distribution, analytics and monetization. The Company's advertising sales organization, which operates as SiriusXM Media, leverages its scale, cross-platform sales organization and ad tech capabilities to deliver results for audio creators and advertisers. SiriusXM, through SiriusXM Canada Holdings, Inc., also offers satellite radio and audio entertainment in Canada. In addition to its audio entertainment businesses, SiriusXM offers connected vehicle services to automakers.

About the Role

As a Senior Machine Learning Engineer at SiriusXM, you will bring machine learning models from development and experimentation to reliable, scalable production systems. You will work closely with Data Scientists, Data Engineers, Platform Engineers, and Services teams to productionize models, build robust feature pipelines, and ensure models operate reliably in live environments. This is a hands-on engineering role with ownership across deployment, serving, monitoring, and lifecycle management of ML systems.

Responsibilities

Model Productionization and Deployment

• Lead the deployment of ML models into production using Databricks and MLFlow, ensuring high performance and integration with existing systems.
• Implement scalable and reliable model serving solutions (both batch and real-time).
• Design and maintain CI/CD pipelines for automated build, test, validation, and deployment of ML artifacts.
• Support safe rollout and rollback strategies across environments.

Feature Engineering and Serving

• Translate feature definitions from data scientists into production-grade pipelines.
• Build and maintain reliable feature serving systems to ensure consistency between training and inference environments.
• Optimize feature pipelines for performance, maintainability, and scalability.

Model Lifecycle Management

• Support model registration, versioning, publishing, and promotion.
• Implement retraining pipelines and redeploy improved models as data and algorithms evolve.
• Participate in the decommissioning and retirement of models.

Reliability, Observability, and Performance

• Ensure production models meet latency, throughput, and reliability requirements.
• Implement logging, monitoring, and alerting of ML systems.
• Investigate and resolve issues related to model performance, deployments, and infrastructure.
• Contribute to operational runbooks and documentation.

Cross-Functional Collaboration

• Work closely with data scientists, engineers, and other stakeholders, providing ML engineering and operations expertise and support.

Best Practices Implementation

• Spearhead the adoption of industry best practices in ML engineering and operations, focusing on areas like version control, data governance, and resource optimization.

Problem Resolution

• Identify and resolve complex issues in ML model performance, deployment, and operational workflows.

Requirements

• Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Experience: 5+ years of experience in ML Engineering, MLOps, data engineering, or a similar role.
• ML Knowledge: Working knowledge of ML models and algorithms.
• Tools & Frameworks: 2+ years of experience with Databricks, MLFlow, and other relevant ML tools and frameworks.
• Programming Languages: Proficiency in Python, Scala, or Java.
• Cloud & Containerization: Experience with cloud platforms (AWS, Azure, etc.) and containerization technologies (Docker, Kubernetes).
• Infrastructure: Familiarity with infrastructure-as-code tooling and practices, e.g., CDK, Terraform.
• Soft Skills: Excellent analytical, problem-solving, and communication skills.

Equal Opportunity

Our goal at SiriusXM is to provide and maintain a work environment that fosters mutual respect, professionalism and cooperation. SiriusXM is an equal opportunity employer that does not discriminate on the basis of actual or perceived race, creed, color, religion, national origin, ancestry, alienage or citizenship status, age, disability or handicap, sex, gender identity, marital status, familial status, veteran status, sexual orientation or any other characteristic protected by applicable federal, state or local laws.

The requirements and duties described above may be modified or waived by the Company in its sole discretion without notice.