Engineer AI

Academy Sports & Outdoors, Inc.•Katy, TX

33d•Onsite

About The Position

The Artificial Intelligence (AI) Engineer designs, develops, and deploys machine learning and deep learning models for enterprise applications. This role involves collaborating with cross-functional teams, leveraging cloud AI platforms, and applying MLOps practices. Key responsibilities include data preprocessing, model optimization, performance monitoring, and ensuring responsible AI standards. The ideal candidate has 4+ years of experience with frameworks like TensorFlow or PyTorch, strong Python skills, and a solid understanding of AI integration into business processes.

Requirements

4+ years of experience in AI/ML model development using frameworks such as TensorFlow, PyTorch, and Scikit-learn.
Hands-on experience in training, validating, and deploying machine learning and deep learning models.
Experience working with cloud AI platforms like Azure ML, AWS SageMaker, or GCP Vertex AI.
Experience in data preprocessing, feature engineering, and model optimization.
Experience collaborating with cross-functional teams to deliver AI-powered solutions.
Familiarity with MLOps practices and tools for model lifecycle management.
Experience with data integration and engineering for AI applications.
Strong programming skills in Python and experience with ML libraries.
Ability to analyze model performance and improve accuracy and efficiency.
Self-motivated and able to work independently on multiple AI projects.
Experience with data science tools and platforms, including Jupyter, SQL, and cloud services.
Excellent communication and documentation skills.
Strong problem-solving and debugging skills for AI models.
Understanding of responsible AI practices and data privacy.
Acceptable level of hearing and vision to perform job duties.
Adhere to company work hours, policies, procedures, and rules governing professional staff behavior.
Regular office attendance is required.

Responsibilities

Design, develop, and deploy AI models for enterprise applications.
Collaborate with data scientists and engineers to build scalable AI solutions.
Perform data analysis and feature engineering for model development.
Monitor and evaluate model performance and retrain as needed.
Document model architecture, training process, and evaluation metrics.
Stay updated with the latest AI research and technologies.
Ensure compliance with responsible AI standards and practices.
Contribute to innovation by experimenting with new AI methodologies such as generative AI and agentic frameworks.
Participate in peer reviews and knowledge-sharing sessions within the AI team.
Support integration of AI models into business processes and applications.
Work with stakeholders to understand requirements and deliver impactful AI solutions.