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Senior Staff Machine Learning Engineer

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting

What you’ll work on

Full 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

From the employer’s posting
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.

What you’ll bring

All qualifications

Core experience

  • 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.
Qualification wording
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.
Education & alternatives
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.
Apply at Sirius XM

Posting record

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Status in our records
Live
First seen by us
Oct 6, 202630 days ago
Recorded sightings
35
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 30

Similar jobs usually come down between day 6 and day 70.

From 4,523 similar postings that came down. Coming down is not always a hire.

Sirius XM is hiring

7 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add 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.

  • Java
  • Python
  • Scala
  • AWS
  • Azure
  • Databricks
  • Docker
  • Kubernetes
  • MLflow
  • Terraform
Where the posting names them
- 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.

Your next step

Complete your application on international-siriusxmradio.icims.com. The employer’s form will show what is required.

Applying through iCIMS

  • You start with your email. New applicants then create a login, and returning ones sign in.
  • Upload your resume before you fill anything in: iCIMS fills some profile fields from it.
  • Check your status on the employer’s iCIMS Dashboard, under Past Job Submittals.

Already applied? Track this application

About Sirius XM

People
About 500 in 2025, down 15% from the year before.Annual report (SEC Form 10-K)
Company
Listed as SIRI.

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 625, the most 1,094, and the latest week had 876.
August 17Last week

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.

About the role

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.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

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.

Job description

View original posting ↗

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.

R-2026-03-61
Source details

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Pay

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Location & working pattern

Dublin, Ireland

Working pattern and location restrictions need checking in the full posting.

Work authorization
- 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.

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