Senior Staff Machine Learning Engineer

About SiriusXM

SiriusXM, alongside its brands including Pandora, SiriusXM Media, AdsWizz, Simplecast, and SiriusXM Connect, is pioneering a transformative era in audio entertainment by delivering compelling subscription and ad-supported audio experiences. Accessible anywhere—whether in vehicles, homes, or through connected devices—our vision is to shape the future where everyone can seamlessly connect to the voices, stories, and music they cherish.

Our recently inaugurated technology hub in Dublin, Ireland, plays a vital role in the ongoing digital transformation and stands as a center of excellence for SiriusXM's global Product and Technology division. The Dublin team concentrates primarily on software development, automotive tech and engineering, AdTech, data science, and analytics. This talent pool is responsible for setting top-tier standards for high-quality, scalable software deployments supporting SiriusXM's streaming and in-vehicle platforms.

Position Impact and Responsibilities

As a Senior Staff Machine Learning Engineer, you will spearhead the progression of machine learning models from research and development into robust, scalable production environments. Collaboration with Data Scientists, Data Engineers, Platform Engineers, and Services teams is essential to productionize models, develop reliable feature pipelines, and ensure stable operation of models in live applications. This role requires active hands-on engineering with responsibility over deployment, maintenance, monitoring, and the lifecycle of ML solutions.

• Lead the deployment of machine learning models into production utilizing Databricks and MLFlow tools to achieve optimal performance and seamless integration.
• Create and sustain scalable model serving frameworks for both batch and real-time processing.
• Engineer CI/CD pipelines facilitating automated building, testing, validation, and deployment of ML components.
• Manage deployment strategies including safe rollout and rollback methods across environments.
• Construct production-grade feature engineering pipelines grounded on definitions provided by data science teams.
• Maintain dependable feature serving systems to guarantee consistency between model training and inference stages.
• Enhance the scalability, maintainability, and efficiency of feature pipelines.
• Oversee model registration, version control, publishing procedures, and promotion workflows.
• Implement continuous retraining pipelines and redeploy updated models reflecting evolving data and algorithms.
• Participate in sunsetting and retiring outdated or obsolete models.
• Guarantee production models meet requirements for latency, throughput, and overall reliability.
• Install and maintain logging, monitoring, and alert systems to uphold ML infrastructure observability.
• Analyze and troubleshoot issues affecting model behavior, deployment quality, and infrastructure stability.
• Contribute to comprehensive operational runbooks and maintain clear documentation.
• Collaborate cross-functionally with technical and business stakeholders to provide expert ML engineering support.
• Champion industry best practices for ML engineering and operational excellence, including version control, data governance, and resource optimization.

Candidate Profile and Skills Required

• Possess a Bachelor's or Master's degree in Computer Science, Engineering, or a closely related discipline.
• Bring 8 or more years of experience in machine learning engineering, MLOps, data engineering, or analogous fields.
• Demonstrate comprehensive understanding of ML algorithms and model architectures.
• Show extensive experience (8+ years) working with Databricks, MLFlow, and pertinent ML platforms and tools.
• Be adept in programming languages such as Python, Scala, or Java.
• Have mastery of cloud computing environments like AWS or Azure, as well as container orchestration technologies including Docker and Kubernetes.
• Be proficient with infrastructure-as-code utilities and methodologies like CDK and Terraform.
• Exhibit strong analytical thinking, problem-solving capabilities, and effective communication skills.

Diversity and Equal Opportunity

SiriusXM is committed to cultivating a working environment promoting mutual respect, professionalism, and cooperative efforts. The company is an equal opportunity employer and prohibits discrimination based on race, color, religion, national origin, age, disability, gender identity, marital status, veteran status, sexual orientation, or any legally protected characteristic.

Additional Information

The listed qualifications and responsibilities may be adjusted or waived by SiriusXM at their sole discretion without prior notice.