9 hours ago
Dublin, IrelandSenior
Responsibilities
- Deploy machine learning models to production using Databricks and MLflow.
- Implement scalable batch and real-time model serving solutions.
- Build and maintain feature engineering and feature serving pipelines.
- Manage model registration, versioning, publishing, promotion, retraining, and retirement.
- Implement monitoring, logging, alerting, and performance improvements for production ML systems.
- Design CI/CD pipelines and safe rollout and rollback strategies.
- Investigate and resolve model, deployment, infrastructure, and operational issues.
- Collaborate with data scientists, data engineers, platform engineers, services teams, and other stakeholders.
- Promote best practices in ML engineering, version control, data governance, and resource optimization.
Requirements
- Bachelor’s or master’s degree in Computer Science, Engineering, or a related field.
- At least 5 years of experience in ML Engineering, MLOps, data engineering, or a similar role.
- At least 2 years of experience with Databricks, MLflow, and other relevant ML tools and frameworks.
- Working knowledge of machine learning models and algorithms.
- Proficiency in Python, Scala, or Java.
- Experience with cloud platforms such as AWS or Azure.
- Experience with Docker and Kubernetes.
- Familiarity with infrastructure-as-code tooling and practices, such as CDK or Terraform.
- Strong analytical, problem-solving, and communication skills.
Categories
About SiriusXM
SiriusXM provides satellite and streaming audio for listeners, including music, sports, news, talk, and podcasts. It sells subscriptions for in-car and mobile listening and operates ad-supported services through Pandora and the SiriusXM Media advertising platform; related brands include AdsWizz and Simplecast. The company is headquartered in New York and trades on Nasdaq as SIRI, with distribution built into many new vehicles via its SiriusXM Connect technology.