Senior Manager - AI

7-Eleven•Irving, TX

8d•Onsite

About The Position

7-Eleven is seeking a Senior Manager, AI, to join its Enterprise AI Team, a multidisciplinary group of scientists, researchers, and engineers that develops data and AI products. The Senior Manager leads technical direction, guides developers, coordinates and delivers large work spanning multiple systems, and communicates progress with product and design partners. The role also involves coaching and mentoring team members, resolving technical and product-process issues, and helping reports increase their impact across the organization. Most senior managers in this role typically spend 0–10% of their time programming, focusing primarily on architecture and planning, mentoring, team morale, budget management, and communication with internal and external stakeholders. The position leads the development and delivery of AI and machine-learning solutions for retail business challenges, from research and prototyping through production deployment. It establishes practices for model development and operations, oversees ML pipelines and infrastructure, ensures data quality and model performance, and partners with business stakeholders to align initiatives with strategic goals. The role is onsite in Irving, Texas, and is not eligible for sponsorship.

Requirements

Bachelor's degree in computer science, machine learning, statistics, mathematics, or a related field.
At least 8 years of experience in machine-learning or data-science roles.
At least 2 years of experience in a technical managerial role.
At least 2 years managing a team of machine-learning engineers or data scientists in a management or technical capacity, with demonstrated delivery.
Strong understanding of data-science and machine-learning foundations, with experience building applications involving natural language processing, structured tabular data, and/or computer vision.
Experience across the full machine-learning lifecycle, from data collection to model deployment, including delivery of ML projects with measurable business impact.
Strong knowledge of deploying AI/ML applications in production, including feature engineering, model selection, model deployment, and MLOps.
Strong understanding of LLM models, LLM engineering architecture, and the ecosystem, including context, tools, skills, and harness, with demonstrated delivery.
Position is not eligible for sponsorship.

Nice To Haves

Master's or PhD degree.
Experience managing, coaching, and mentoring people, with demonstrated ability to build team culture.
Experience in retail, e-commerce, or consumer-facing technology.
Experience with Databricks.
Experience successfully building and scaling custom chatbots and multi-agent systems.

Responsibilities

Lead research, prototyping, and development of AI solutions for retail business challenges.
Manage the full lifecycle of machine-learning projects, from conception through production deployment.
Establish best practices for model development, validation, deployment, and monitoring.
Mentor and coach team members to improve technical skills and career growth.
Partner with business stakeholders to align machine-learning initiatives with strategic objectives.
Oversee development of ML pipelines and infrastructure to support scalable model deployment.
Ensure high standards for data quality, model performance, and ethical AI practices.
Evaluate and recommend machine-learning technologies, frameworks, and approaches.
Stay current with emerging AI/ML technologies and research to drive innovation.
Communicate complex technical concepts effectively to non-technical stakeholders.
Manage project timelines, resources, and deliverables to ensure successful implementation.
Guide developers, coordinate delivery of large tasks spanning multiple systems, and communicate team progress alongside the Product Manager and Design Lead.
Coach and mentor direct reports and help resolve technical and product-process issues.
Contribute to architecture and planning, team morale, budget management, and communication with internal and external stakeholders.