ML Engineer, Production-Scale AI & Cloud Solutions

UPS; Atlanta (GA); On-site; USD 120,000 - 190,000; Full time

Job summary

UPS in Atlanta seeks a seasoned ML Engineer to design, build, test, and deploy ML models and software components that power business outcomes across the organization. You will collaborate with data science, product, architecture, and engineering teams to scale data pipelines, productionize models, and deliver end-to-end AI solutions on cloud platforms.

This permanent role requires strong communication, cross-functional teamwork, and the ability to translate complex analytics into practical value

Qualifications

• Experience designing and building data-intensive solutions using distributed computing.
• Familiarity with ML frameworks (Keras, PyTorch) and libraries (scikit-learn).
• Experience productionizing ML models for batch and streaming use.

Responsibilities

• Studies and transforms data science prototypes into ML systems.
• Researches and implements ML algorithms and tools per business requirements.
• Collaborates with teams to deliver ML products and systems.
• Designs workflows to scale ML model development.
• Creates and evolves ML models and software enabling AI systems.
• Extends ML libraries with new developments.
• Configures scalable cloud components for prediction transactions.
• Integrates data from internal/external sources for data products.

Skills

Distributed computing

ML/AI frameworks

Cloud architectures

Statistics & modeling

Cross-functional teamwork

Communication

Education

BS/BA in quantitative field

Tools

Keras

PyTorch

scikit-learn

Cloud AI technologies

Job description

UPS in Atlanta seeks a seasoned ML Engineer to design, build, test, and deploy ML models and software components that power business outcomes across the organization. You will collaborate with data science, product, architecture, and engineering teams to scale data pipelines, productionize models, and deliver end-to-end AI solutions on cloud platforms.

This permanent role requires strong communication, cross-functional teamwork, and the ability to translate complex analytics into practical value