AI/ML Engineer - Senior Level

USAA•San Antonio, NC

4d•$143,320 - $273,930

About The Position

As a dedicated AI/ML Engineer at the senior level, you will participate in all phases of data management and machine learning lifecycles, including requirements analysis, data collection and processing, statistical analysis, model-performance monitoring, and compliance with related risk requirements. You will develop and maintain technical systems that use machine learning models to make predictions for classification and decision-making. You will consult with data scientists and business partners on machine-learning development and implementation, provide technical feedback, and lead machine-learning engineering across analysis, solution design, data pipeline engineering, testing, deployment, scheduling, application integration, production support, and API development. The work supports generative AI applications, machine-learning frameworks and libraries, and ML models. You will configure and manage AI/ML infrastructure in cloud and on-premises environments, work with architects on implementation patterns, design and prototype complex solutions, and help set technical direction while mentoring team members. You will also ensure business risks are identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.

Requirements

Bachelor's degree, or four years of relevant education and/or experience.
Six years of machine-learning engineering, data engineering, or software development experience implementing data solutions, including two years of demonstrated technical leadership experience and/or leading teams.
Extensive programming experience using Python, Java, or R.
Extensive data engineering experience.
Experience delivering end-to-end machine-learning and AI/generative AI solutions, including building, integrating, and optimizing data pipelines; curating and modeling data for different consumers, products, and usage patterns; and working with data marts, data lakes, and operational analytic applications.
Experience completing multiple projects using Agile methodology to implement machine-learning models.
Experience leveraging MLOps principles and implementing automated workflows.
Demonstrated ability to mentor junior technical team members in an area of expertise.
Knowledge of data science principles and methodologies.
Knowledge of stochastic modeling, machine learning, and other advanced mathematical techniques.
Effective communication skills, including presenting complex technical concepts to technical and non-technical audiences.
Expert knowledge of at least one cloud platform and its relevant components, such as AWS SageMaker.

Responsibilities

Consult with data scientists and business partners on approaches to machine-learning model development and implementation.
Provide technical feedback on machine-learning solutions within the technical lead community.
Lead the full machine-learning engineering lifecycle, including analysis, solution design, data pipeline engineering, testing, deployment, scheduling, application integration, production support, and API development.
Support generative AI applications, machine-learning frameworks and libraries, and machine-learning models.
Configure, manage, and set up AI/ML infrastructure components in cloud and on-premises environments, including AWS, GCP, and graph databases.
Work with architects to influence and define machine-learning model implementation patterns in complex environments.
Apply appropriate design patterns throughout solution design and implementation based on complex model implementation requirements.
Design and implement complex technical solutions for machine learning, artificial intelligence, and generative AI.
Create proofs of concept and prototypes for highly complex solutions and present them to leadership.
Assist in setting the team's technical direction and mentor team members.
Ensure business risks are identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.