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Dublin, Ireland
Live, first seen by us 30 days agoEmployment type in the employer’s posting: FULL_TIMEFrom the employer’s posting
Deploy ML models into production on Databricks and MLFlow, with batch and real-time serving
Build and maintain CI/CD pipelines for automated ML build, test and deployment
Turn data scientists' feature definitions into production feature pipelines and serving systems
Implement retraining pipelines and redeploy improved models
Implement logging, monitoring and alerting for ML systems
Lead the deployment of ML models into production using Databricks and MLFlow
Design and maintain CI/CD pipelines for automated build, test, validation, and deployment of ML artifacts.
Translate feature definitions from data scientists into production-grade pipelines.
Implement retraining pipelines and redeploy improved models as data and algorithms evolve.
Implement logging, monitoring, and alerting of ML systems.
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.
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.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 30
Similar jobs usually come down between day 6 and day 70.
From 4,595 similar postings that came down. Coming down is not always a hire.
7 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 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).
- 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
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).
- 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.
Complete your application on international-siriusxmradio.icims.com. The employer’s form will show what is required.
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New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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
Feature Engineering and Serving
Model Lifecycle Management
Reliability, Observability, and Performance
Cross-Functional Collaboration
Best Practices Implementation
What you'll need:
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.
R-2026-03-61Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
Dublin, Ireland
Working pattern and location restrictions need checking in the full posting.
- 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.