Staff Machine Learning Ops Engineer

$101,000 - $200,050/Yr

Sirius XM Canada - Lawrence Township, NJ

Full-time - Senior

Lawrence Township, NJ

About the position

As a Staff Machine Learning Ops Engineer at SiriusXM, you will play a crucial role in our Data Platform Team, focusing on deploying, managing, and optimizing machine learning (ML) models. This position is pivotal in ensuring the scalability and effectiveness of our ML initiatives, which are integral to our data-driven strategies and the continuous enhancement of our audio services. You will leverage advanced tools such as Databricks and MLFlow to lead the deployment of ML models into production, ensuring high performance and seamless integration with existing systems. Your responsibilities will include continuously monitoring and maintaining the health of ML models, optimizing them for efficiency and effectiveness. You will design and implement automated ML pipelines for model training, evaluation, and deployment, working closely with data scientists, engineers, and other stakeholders to provide ML Ops expertise and support. Additionally, you will spearhead the adoption of industry best practices in ML operations, focusing on version control, data governance, and resource optimization. Staying ahead of the curve is essential, as you will research and implement emerging technologies and methodologies in the ML Ops field, while also identifying and resolving complex issues in ML model performance, deployment, and operational workflows.

Responsibilities

• Lead the deployment of ML models into production using Databricks and MLFlow, ensuring high performance and integration with existing systems.
• Continuously monitor and maintain the health of ML models, optimizing them for efficiency and effectiveness.
• Design and implement automated ML pipelines for model training, evaluation, and deployment, utilizing Databricks and MLFlow.
• Work closely with data scientists, engineers, and other stakeholders, providing ML Ops expertise and support.
• Spearhead the adoption of industry best practices in ML operations, focusing on areas like version control, data governance, and resource optimization.
• Stay ahead of the curve by researching and implementing emerging technologies and methodologies in the ML Ops field.
• Identify and resolve complex issues in ML model performance, deployment, and operational workflows.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 7+ years' experience in ML Ops, data engineering, or a similar role.
• Deep knowledge of ML models and algorithms.
• Expertise in Databricks, MLFlow, and other relevant ML tools and frameworks.
• Proficiency in programming languages such as Python, Scala, or Java.
• Strong experience with cloud platforms (AWS, Azure, etc.) and containerization technologies (Docker, Kubernetes).
• Excellent analytical, problem-solving, and communication skills.
• Must have legal right to work in the U.S.

Benefits

• Discretionary short-term and long-term incentives based on performance.