Offices at Ahold Delhaize USA

Ahold Delhaize USA is headquartered in Chicago, Illinois, USA and has 7 office locations.

Hybrid Workplace

Employees engage in a combination of remote and on-site work.

Typical time on-site: 3 days a week

U.S. Office Locations

HQ
Chicago, Illinois, USA

Right next to Union Station, we are easy to get to and surrounded by food in Downtown and the West Loop.

Carlisle, Pennsylvania, USA

1149 Harrisburg Pike, Carlisle, PA, United States, 17013

Landover, Maryland, USA

8301 Professional Place, Suite 115, Landover, MD, United States, 20785

Mauldin, South Carolina, USA
Mauldin, SC

211 Bi-Lo Boulevard , Mauldin, SC, United States, 29607

Quincy, Massachusetts, USA

1385 Hancock St, Quincy, MA, United States, 02169

Salisbury, North Carolina, USA

2110 Executive Dr, Salisbury, NC, United States, 28147

Scarborough, Maine, USA

145 Pleasant Hill Rd., Scarborough, ME, United States, 04074

Search the 387 jobs at Ahold Delhaize USA

AdTech • eCommerce • Food • Marketing Tech • Retail
The Senior Engineering Manager for Master Data will oversee the development and implementation of enterprise MDM systems, collaborate with IT teams, manage a team of engineers, and ensure data quality and compliance with standards. This role requires technical expertise in MDM and related technologies, with a focus on mentoring and team development.
22 Hours Ago
Hyattsville, MD, USA
AdTech • eCommerce • Food • Marketing Tech • Retail
The IT Engineer ML Ops role involves designing and deploying scalable ML infrastructure, creating automated pipelines for training and monitoring ML models, and collaborating with cross-functional teams to enhance model lifecycle management. The position requires proficiency in programming languages and a strong understanding of machine learning principles.
22 Hours Ago
Scarborough, ME, USA
AdTech • eCommerce • Food • Marketing Tech • Retail
The IT Engineer ML Ops will design and deploy scalable infrastructure for machine learning workloads, develop automated pipelines, validate ML models, optimize code for production, and mentor team members. They will collaborate with data scientists and engineers to enhance ML applications and infrastructure.