Senior Staff Machine Learning Engineer

AdsWizz; Dublin; On-site; EUR 140,000 - 190,000; Full time

Job summary

SiriusXM is hiring a Senior Staff ML Engineer in our Dublin hub to bring ML models from experimentation to scalable production. You will own deployment, feature pipelines, and monitoring, coordinating with Data Scientists and Platform Engineers to ensure reliability and performance in live environments.

You will leverage Databricks, MLFlow, and cloud platforms (AWS/Azure) with Docker/Kubernetes, implementing robust CI/CD for ML artifacts and contributing to operational runbooks and best

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 8+ years of experience in ML Engineering, MLOps, data engineering, or a similar role.
• Deep knowledge of ML models and algorithms.

Responsibilities

• Lead productionization and deployment of ML models with scalable serving.
• Build robust feature pipelines and ensure alignment between training and inference.
• Design and maintain CI/CD pipelines for ML artifacts.
• Implement monitoring, logging, and alerting for live models.
• Collaborate with data scientists and engineers across teams.

Skills

ML engineering

MLOps

Databricks

MLFlow

Python

Scala/Java

Cloud platforms (AWS/Azure)

Docker

Kubernetes

CI/CD

Education

Bachelor's or Master's degree in Computer Science, Engineering, or related field

Tools

Databricks

MLFlow

Docker

Kubernetes

CI/CD tooling

Job description

Who we are:

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.

We are proud to have launched a new state-of-the-art technology facility in Dublin, Ireland. The Dublin-based team plays a critical role in our continued digital transformation and will function as a center of excellence for SiriusXM's global Product and Technology organization.

SiriusXM's new Dublin facility will comprise a workforce primarily focused on software development, automotive technology and engineering, AdTech, data science, and analytics. Talent based in the new technology hub will be charged with developing and implementing best-in-class standards for high-quality, scalable software deliveries for SiriusXM's streaming and in-vehicle audio entertainment platforms.

How you'll make an impact:

As a Senior Staff ML 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.

What you'll do:

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.

What you'll need:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 8+ years of experience in ML Engineering, MLOps, data engineering, or a similar role.
• Deep knowledge of ML models and algorithms.
• 8+ years of experience with Databricks, MLFlow, and other relevant ML tools and frameworks.
• Proficiency in programming languages such as Python, Scala, or Java.
• Mastery of cloud platforms (AWS, Azure, etc.) and containerization technologies (Docker, Kubernetes).
• Expert with infrastructure‑as‑code tooling and practices, e.g., CDK, Terraform
• Excellent analytical, problem‑solving, and communication skills.

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.