Lead AI Engineer - AI Platform

Lowes•Charlotte, NC

1d•Onsite

About The Position

The primary purpose of this role is to lead artificial intelligence (AI) engineering initiatives and the development of AI solutions that enable the integration and evolution of advanced machine learning (ML) models, including deep learning (DL) frameworks and large language models (LLMs). The Lead AI Engineer will be responsible for leading the advancement of model performance, implementing essential tools and frameworks, and optimizing compute and storage solutions to elevate AI technologies to new heights.

Requirements

Bachelor’s degree in science, technology, engineering, math, or related field or equivalent years of experience in lieu of education requirement, if applicable
6 years of experience executing and deploying data science, ML, and DL (fewer years may be accepted with a Master's or Doctorate degree), ML platform engineering, MLOps tools, and ML frameworks
6 years of programming experience in Java and/or Python
4 years of experience working with cross-functional partners

Nice To Haves

Master’s degree in science, technology, engineering, math, statistics, physics, economics, data science, information science, or quantitative analytics
5 years of experience in SQL and NoSQL databases, Hadoop ecosystem, Druid, Trino, Big Query, Google Vertex AI
6 years of Python programming experience.
2 years of experience in AI technology.

Responsibilities

Leads the development of the AI platform and ensures the scalability of the platform accommodates a wide spectrum of AI models and integration of new AI advancements as APIs.
Leads the architectural design, development, and implementation of sophisticated tools and frameworks that elevate ML experimentation and deployment, ensuring that the platform delivers high-end AI functionalities.
Architects and orchestrates the management of graphics processing unit and central processing unit resources to enhance the performance of AI models while maximizing cost efficiency and resource utilization.
Mentors and guides junior team members to ensure a seamless integration of AI models into the platform.
Leads the creation and management of robust data movement strategies and pipelines, optimizing data flows to meet the requirements of intensive AI model training and inference processes.
Leads initiatives for continuous improvement by evaluating platform performance analytics and gathering user feedback.
Leads cross-functional teams, fostering a collaborative environment that merges deep technical knowledge with strategic business insights and a keen understanding of user needs.
Champions the development and enforcement of rigorous security protocols and governance measures for the AI platform, ensuring data integrity and adherence to industry standards and best practices.