SiriusXM

Pandora, a subsidiary of SiriusXM, is the largest ad-supported audio entertainment streaming service in the U.S. SiriusXM's subsidiaries Simplecast and AdsWizz make it a leader in podcast hosting, production, distribution, analytics, and monetization.. As a Senior ML Ops Engineer at SiriusXM, you will be a key player in our Data Platform Team. Your role will be pivotal in deploying, managing, and optimizing machine learning (ML) models, leveraging advanced tools like Databricks and MLFlow.. Lead the deployment of ML models into production using Databricks and MLFlow, ensuring high performance and integration with existing systems.. Design and implement automated ML pipelines for model training, evaluation, and deployment, utilizing Databricks and MLFlow.. Expertise in Databricks, MLFlow, and other relevant ML tools and frameworks.

operations engineer

Who We Are SiriusXM and its brands (Pandora, SiriusXM Media, AdsWizz, Simplecast, and SiriusXM Connected Vehicle Services) 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. This is the place where a diverse group of emerging talent and legends alike come to share authentic and purposeful songs, stories, sounds and insights through some of the best programming and technology in the world. Our critically acclaimed, industry-leading audio entertainment encompasses music, sports, comedy, news, talk, live events, and podcasting. No matter their individual role, each of our employees plays a vital part in bringing SiriusXM’s vision to life every day. SiriusXM is the leading audio entertainment company in North America, and the premier programmer and platform for subscription and digital advertising-supported audio products. SiriusXM’s platforms collectively reach approximately 150 million listeners, the largest digital audio audience across paid and free tiers in North America, and deliver music, sports, talk, news, comedy, entertainment, and podcasts. Pandora, a subsidiary of SiriusXM, is the largest ad-supported audio entertainment streaming service in the U.S. SiriusXM's subsidiaries Simplecast and AdsWizz make it a leader in podcast hosting, production, distribution, analytics, and monetization. The Company’s advertising sales organization, which operates as SiriusXM Media, leverages its scale, cross-platform sales organization, and ad tech capabilities to deliver results for audio creators and advertisers. SiriusXM, through Sirius XM Canada Holdings, Inc., also offers satellite radio and audio entertainment in Canada. In addition to its audio entertainment businesses, SiriusXM offers connected vehicle services to automakers. How You’ll Make An Impact As a Senior ML Ops Engineer at SiriusXM, you will be a key player in our Data Platform Team. Your role will be pivotal in deploying, managing, and optimizing machine learning (ML) models, leveraging advanced tools like Databricks and MLFlow. You will ensure the scalability and effectiveness of our ML initiatives, contributing significantly to our data-driven strategies and the continual enhancement of our audio services. What You’ll Do <ul><li>Lead the deployment of ML models into production using Databricks and MLFlow, ensuring high performance and integration with existing systems.</li><li>Continuously monitor and maintain the health of ML models, optimizing them for efficiency and effectiveness.</li><li>Design and implement automated ML pipelines for model training, evaluation, and deployment, utilizing Databricks and MLFlow.</li><li>Work closely with data scientists, engineers, and other stakeholders, providing ML Ops expertise and support.</li><li>Spearhead the adoption of industry best practices in ML operations, focusing on areas like version control, data governance, and resource optimization.</li><li>Stay ahead of the curve by researching and implementing emerging technologies and methodologies in the ML Ops field.</li><li>Identify and resolve complex issues in ML model performance, deployment, and operational workflows. </li></ul>What You’ll Need <ul><li>Bachelor’s or master’s degree in Computer Science, Engineering, or a related field.</li><li>5+ years’ experience in ML Ops, data engineering, or a similar role.</li><li>Deep knowledge of ML models and algorithms.</li><li>Expertise in Databricks, MLFlow, and other relevant ML tools and frameworks.</li><li>Proficiency in programming languages such as Python, Scala, or Java.</li><li>Strong experience with cloud platforms (AWS, Azure, etc.) and containerization technologies (Docker, Kubernetes).</li><li>Excellent analytical, problem-solving, and communication skills.</li><li>Must have legal right to work in the U.S. </li></ul>At SiriusXM, we carefully consider a wide range of factors when determining compensation, including your background and experience. These considerations can cause your compensation to vary. We expect the base salary for this position to be in the range of $135,000 to $209,500 and will depend on your skills, qualifications, and experience. Additionally, this role might be eligible for discretionary short-term and long-term incentives. We encourage all interested candidates to apply. 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-2024-05-40

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