Staff Machine Learning Engineer

About SiriusXM

SiriusXM along with its related brands Pandora, AdsWizz, Simplecast, and SiriusXM Connect, is pioneering the audio entertainment landscape by providing leading subscription and ad-supported audio experiences accessible in cars, homes, and on portable connected devices. Its vision is to seamlessly connect audiences to cherished voices, stories, and music wherever they are.

Our team is a blend of rising talents and industry veterans who contribute authentic content across multiple audio genres such as music, sports, comedy, news, talk, live events, and podcasts, supported by world-class programming and technology. Every team member plays an essential role in realizing this vision daily.

We are inaugurating a cutting-edge technology center in Dublin, Ireland, serving as a hub for product and technology innovation globally. This facility will emphasize software development, automotive technology, AdTech, data science, and analytics, with a mandate to establish best-in-class scalable software standards for SiriusXM's streaming and in-vehicle audio platforms.

Role Responsibilities

• Lead the deployment and productionization of machine learning models using tools like Databricks and MLFlow, ensuring integration with current systems and optimal performance.
• Develop and maintain scalable and dependable batch and real-time model serving solutions.
• Create and manage automated CI/CD pipelines for building, testing, validating, and deploying ML models.
• Design safe rollout and rollback mechanisms across different environments.
• Convert feature definitions from data science teams into scalable, maintainable production pipelines and feature serving systems ensuring consistency between training and inference.
• Manage the model lifecycle, including registration, versioning, publishing, promotion, retraining pipelines, redeployment with updated data and algorithms, and orderly decommissioning.
• Ensure models meet performance benchmarks such as latency, throughput, and reliability by implementing rigorous logging, monitoring, and alerting systems.
• Investigate and troubleshoot issues related to model performance, deployment, or infrastructure, and document operational procedures and runbooks.
• Collaborate cross-functionally with data scientists, engineers, and other stakeholders to provide ML engineering expertise and facilitate smooth operations.
• Drive implementation of industry best practices in ML engineering, including version control, data governance, and resource optimization.
• Identify and resolve complex problems affecting ML systems, deployment workflows, and performance.

Qualifications and Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or relevant disciplines.
• At least 7 years of professional experience in machine learning engineering, MLOps, or data engineering roles.
• In-depth understanding of machine learning models and algorithms.
• Minimum of 4 years’ expertise with Databricks, MLFlow, and comparable ML platforms and frameworks.
• Proficient in programming languages such as Python, Scala, or Java.
• Strong background in cloud platforms (AWS, Azure, et al.) and container orchestration technologies including Docker and Kubernetes.
• Experience with infrastructure-as-code tools and methodologies (e.g., CDK, Terraform).
• Excellent analytical, problem-solving, and communication competencies.

Additional Information

SiriusXM is committed to fostering a workplace characterized by respect, professionalism, and collaboration. We are an equal opportunity employer and do not discriminate on legally protected bases including race, gender identity, age, disability, veteran status, sexual orientation, or any status protected by laws.

The described duties and requirements may be adjusted or waived at the company’s sole discretion without prior notification.