Staff Machine Learning Ops Engineer

$100,000 - $200,050/Yr

Pandora Jewelry - Lawrence Township, NJ

Full-time - Mid Level

Lawrence Township, NJ

Merchant Wholesalers, Durable Goods

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. Your expertise will be essential in leveraging advanced tools such as Databricks and MLFlow to ensure the scalability and effectiveness of our ML initiatives. This position is pivotal in contributing to our data-driven strategies and enhancing our audio services, which are at the forefront of the audio entertainment industry. In this role, you will lead the deployment of ML models into production, ensuring high performance and seamless integration with existing systems. You will continuously monitor and maintain the health of these models, optimizing them for efficiency and effectiveness. Your responsibilities will also include designing and implementing automated ML pipelines for model training, evaluation, and deployment, utilizing Databricks and MLFlow. Collaboration is key, as you will work closely with data scientists, engineers, and other stakeholders, providing ML Ops expertise and support. You will spearhead the adoption of industry best practices in ML operations, focusing on critical areas such as version control, data governance, and resource optimization. Staying ahead of the curve is vital; therefore, you will be expected to research and implement emerging technologies and methodologies in the ML Ops field. Additionally, you will identify and resolve complex issues related to ML model performance, deployment, and operational workflows, ensuring that our audio services remain top-notch and innovative.

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

• Competitive salary range of $101,000 to $200,050 based on skills and experience.
• Eligibility for discretionary short-term and long-term incentives.