Senior Manager Machine Learning - AI/ML & MLOps

Senior Manager Machine Learning - AI/ML & MLOps

What you will do

Lets do this. Lets change the world. In this vital role you will lead and oversee a team of AI/ML engineers to develop and operationalize machine learning capabilities, with a focus on optimizing end-to-end MLOps processes. You will be responsible for handling the entire lifecycle of AI/ML model development, deployment, and monitoring at Amgen.

As a Sr. Manager, you will play a critical role in guiding your team through the implementation of scalable, efficient, and high-quality AI/ML solutions. You will lead the vision, drive innovation, and ensure seamless delivery of data-driven products that enhance decision-making across the organization. Your expertise will be pivotal in helping Amgen evolve its ML operations, ensuring that models are developed, deployed, and maintained in a reliable and scalable manner.

You will play a key role in a regulatory submission content automation initiative which will modernize and digitize the regulatory submission process, positioning Amgen as a leader in regulatory innovation. The initiative uses pioneering technologies, including Generative AI, structured content management, and integrated data to automate the creation, review, and approval of regulatory content.

• Lead delivery of overall AI/ML solutions from concept to production, handling a multi-functional product team comprising AI/ML engineers, data scientists, and MLOps specialists to ensure that business, quality, and functional goals are met.
• Drive excellence and quality across MLOps workflows, ensuring the reliability, scalability, and monitoring of deployed models.
• Design and implement best-in-class MLOps practices to ensure a seamless deployment pipeline and model lifecycle management.
• Be hands-on where necessary to drive quality and best-in-class engineering practices, including automation, CI/CD pipelines, and model monitoring.
• Motivate and encourage your team to deliver innovative and impactful AI/ML solutions.
• Communicate effectively with partners to align on goals and synchronize with the overall business vision.
• Supervise the career development and growth of team members, providing guidance, mentorship, and support.

What we expect of you

As an Information Systems Senior Manager supervising AI/ML engineering, you will be responsible for leading a high-performance team to deliver effective AI/ML model solutions and ensure consistent operation of MLOps capabilities. You will collaborate with key partners, supervise engineering projects, ensure compliance with IT policies and standards, and drive the continuous improvement of AI/ML workflows.

Basic Qualifications:

• Doctorate degree and 2 years of Information Systems experience OR,
• Masters degree and 8 to 10 years of Information Systems experience OR,
• Bachelors degree and 10 to 14 years of Information Systems experience OR,
• Diploma and 14 to 18 years of Information Systems experience.
• 5+ years of managerial experience directly handling people and/or leading teams, projects, or programs.
• In-depth knowledge of Agile process and principles.
• Experience with financial/spend management for small to medium engineering teams is a plus.
• Thorough understanding of AI/ML model development, MLOps practices, data integration, and cloud infrastructure, including AWS, Azure, or GCP.
• Experience in building and leading teams with consistent standards and strong engineering practices.
• Demonstrated experience with AWS, Databricks, and/or Azure MLOps applications and components, including infrastructure setup, model training and deployment, data integration, monitoring, and pipeline management.
• Experience in optimizing workflows with CI/CD pipelines, handling model versioning, and implementing automated retraining mechanisms is crucial.

Preferred Qualifications:

• Design, implement, and handle cloud infrastructure solutions using AWS and/or Azure services, ensuring scalability, security, and reliability.
• Develop and maintain cloud-based applications by using core services like EC2, S3, RDS in AWS or VMs, Azure Blob Storage, and SQL Databases in Azure.
• Use monitoring tools such as AWS CloudWatch or Azure Monitor to ensure high availability and performance of cloud-hosted systems.
• Automate deployment processes using cloud-native tools (e.g., AWS CloudFormation, Azure Resource Manager, or Terraform) to support CI/CD pipelines.

Soft Skills:

Leadership:

• Influences through Collaboration: Builds support for ideas by working collaboratively with others.
• Strategic Thinking: Plans long-term and anticipates downstream impacts of decisions.
• Transparent Decision-Making: Clearly articulates the rationale behind decisions and reflects on successes and failures.
• Adaptive Leadership: Recognizes and leads through changing conditions in technology and operations.