Truist Financial - Charlotte, NC

posted 3 months ago

Part-time,Full-time - Senior
Charlotte, NC
Credit Intermediation and Related Activities

About the position

The Machine Learning Engineering Development Senior Lead position is a critical role within our organization, focusing on the operationalization, management, and continuous improvement of our AI/ML pipelines. This seasoned MLOps professional will work closely with data scientists and engineers to ensure that machine learning models are deployed reliably, monitored effectively, and optimized for maximum business impact. The role requires a deep understanding of both the technical and operational aspects of machine learning, as well as the ability to collaborate across teams to drive MLOps excellence. In this position, you will be responsible for developing and maintaining automated CI/CD pipelines for machine learning models, ensuring seamless transitions from development to production in both AWS and on-premise environments. You will build and manage strategies for deploying models using AWS services such as SageMaker and Bedrock, ensuring that they are scalable and perform optimally. Additionally, you will implement comprehensive monitoring of deployed models, establishing alerts and triggers for proactive maintenance and retraining to address any performance drift. Your role will also involve implementing a streamlined workflow using version control systems like GitHub or Bitbucket, integrated with container repositories and model repositories to enable robust production deployments. Collaboration is key, as you will liaise with data scientists, engineers, and business stakeholders to streamline MLOps processes and ensure that models meet business objectives. Ultimately, your goal will be to continuously enhance models and ensure peak performance at scale, contributing to the overall success of our AI initiatives.

Responsibilities

  • Develop and maintain automated CI/CD pipelines for machine learning models, ensuring seamless transitions from development to production in AWS/on-premise environments.
  • Build and manage strategies to deploy models utilizing SageMaker, Bedrock, and other AWS services, ensuring scalability and performance.
  • Implement comprehensive monitoring of deployed models, establishing alerts and triggers for proactive maintenance and retraining to address performance drift.
  • Implement a streamlined workflow using version control systems (e.g., GitHub, Bitbucket) for code and models, integrated with container repositories and model repositories to enable robust production deployments.
  • Liaise with data scientists, engineers, and business stakeholders to streamline MLOps processes and ensure models meet business objectives.
  • Implement and streamline MLOps processes to continuously enhance models, ensuring peak performance at scale.

Requirements

  • Bachelor's degree in Computer Science, Software Engineering, or a related field.
  • Minimum of 15+ years in software development, with 5+ years focused on MLOps practices.
  • Proven experience working within the financial services industry.
  • In-depth knowledge of Python, Spark, Scala, MLOps tools and frameworks, AWS (SageMaker, Lambda, etc.), containerization, infrastructure as code (Terraform, CloudFormation).

Nice-to-haves

  • Master's degree preferred.
  • AWS or any other cloud provider certifications.

Benefits

  • Medical insurance
  • Dental insurance
  • Vision insurance
  • Life insurance
  • Disability insurance
  • Accidental death and dismemberment insurance
  • Tax-preferred savings accounts
  • 401k plan
  • Vacation days (minimum of 10 days)
  • Sick days (minimum of 10 days)
  • Paid holidays
  • Defined benefit pension plan (depending on position and division)
  • Restricted stock units (depending on position and division)
  • Deferred compensation plan (depending on position and division)
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