Machine Learning Engineer

GSV UPS General Services; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

GSV UPS General Services in Atlanta, GA, seeks a senior ML engineer to design, build, test, and deliver ML models and software components that solve complex business problems. You will collaborate with business, product, architecture, engineering, and data science teams to deploy production-scale solutions using structured and unstructured data.

The role emphasizes developing scalable data pipelines, exploring ML algorithms (Keras, PyTorch, scikit-learn), and implementing end-to-end ML systems

Qualifications

• Experience designing and building data-intensive solutions using distributed computing within a multi-line business environment.
• Familiarity in Machine Learning and AI frameworks (Keras, PyTorch) and libraries (scikit-learn).
• Experience establishing end-to-end solution design components to support batch and live streaming predictions.
• Creative and critical thinking skills in complex problems.
• Productionizing ML models (classification/regression, NLP, deep learning).
• Experience with scalable data processing, feature development, and model optimization.
• Strong understanding of statistics (forecasting, time series, hypothesis testing, classification, clustering).
• Knowledge of SDLM/SDLC, Agile, and cloud infrastructures.

Responsibilities

• Studies and transforms data science prototypes into ML systems using appropriate datasets and data representation models.
• Researches and implements ML algorithms and tools for business requirements.
• Collaborates with teams to deliver ML products and systems for the organization.
• Designs workflows and analysis tools to streamline ML model development at scale.
• Creates and evolves ML models and software enabling state-of-the-art intelligent systems.
• Extends existing ML libraries and frameworks with new developments in DS/ML.
• Establishes, configures, and supports scalable cloud components that serve prediction model transactions.
• Integrates data from authoritative sources to form the foundation of a new Data Product.

Skills

Distributed computing

Keras

PyTorch

scikit-learn

NLP

End-to-end ML

Model optimization

Statistics

Cloud

Agile

Teamwork

Communication

Education

Bachelor’s degree in quantitative field

Job description

Before you apply to a job, select your language preference from the options available at the top right of this page. Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow—people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level.

Job Description: JOB SUMMARY

This position participates in the design, build, test, and delivery of Machine Learning (ML) models and software components that solve challenging business problems for the organization, working in collaboration with the Business, Product, Architecture, Engineering, and Data Science teams. This position engages in assessment and analysis of data sources of structured and unstructured data (internal and external) to uncover opportunities for ML and Artificial Intelligence (AI) automation, predictive methods, and quantitative modeling across the organization. This position establishes and configures scalable and cost-effective end to end solution design pattern components to support prediction model transactions. This position designs trials and tests to measure the success of software and systems, and works with teams, or individually, to implement ML/AI models for production scale.

RESPONSIBILITIES

• Studies and transforms data science prototypes into ML systems using appropriate datasets and data representation models.
• Researches and implements appropriate ML algorithms and tools that creates new systems and processes powered with ML and AI tools and techniques according to business requirements
• Collaborates with others to deliver ML products and systems for the organization.
• Designs workflows and analysis tools to streamline the development of new ML models at scale.
• Creates and evolves ML models and software that enable state-of-the-art intelligent systems using best practices in all aspects of engineering and modelling lifecycles.
• Extends existing ML libraries and frameworks with the developments in the Data Science and Machine Learning field.
• Establishes, configures, and supports scalable Cloud components that serve prediction model transactions
• Integrates data from authoritative internal and external sources to form the foundation of a new Data Product that would deliver insights that supports business outcomes necessary for ML systems.

QUALIFICATIONS

• Experience designing and building data-intensive solutions using distributed computing within a multi-line business environment.
• Familiarity in Machine Learning and Artificial Intelligence frameworks (i.e., Keras, PyTorch), libraries (i.e., scikit-learn), and tools and Cloud-AI technologies that aids in streamlining the development of Machine Learning or AI systems.
• Experience in establishing and configuring scalable and cost-effective end to end solution design pattern components to support the serving of batch and live streaming prediction model transactions
• Possesses creative and critical thinking skills.
• Experience in developing Machine Learning models such as: Classification/Regression Models, NLP models, and Deep Learning models; with a focus on productionizing those models into product features.
• Experience with scalable data processing, feature development, and model optimization.
• Solid understanding of statistics such as forecasting, time series, hypothesis testing, classification, clustering or regression analysis, and how to apply that knowledge in understanding and evaluating Machine Learning models.
• Knowledgeable in software development lifecycle (SDLM), Agile development practices and cloud technology infrastructures and patterns related to product development
• Advanced math skills in Linear Algebra, Bayesian Statistics, Group Theory.
• Works collaboratively, both in a technical and cross-functional context.
• Strong written and verbal communication.
• Bachelors’ (BS/BA) degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience.

OTHER CRITERIA

• This job is a grade 20G.
• Hours of Operation are subject to change: 8:00 AM - 5:00 PM EST.
• Position is located in Atlanta, GA.
• Must be currently located in the same geographic location as the job or willing to self-relocate.
• No Relocation assistance offered.
• Employer will not sponsor visas for position.
• Last day to apply for internal applicants is 11:59 PM EST on 10/17/2026.
• Employee Type: Permanent
• UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.
• UPS is an equal opportunity employer.
• UPS does not discriminate on the basis of race/color/religion/sex/national origin/veteran/disability/age/sexual orientation/gender identity or any other characteristic protected by law.

Basic Qualifications: Must be a U.S. Citizen or National of the U.S., an alien lawfully admitted for permanent residence, or an alien authorized to work in the U.S. for this employer.

Background

In 1907, two teenage entrepreneurs in a Seattle basement started with a $100 loan and created what would become the world’s largest package delivery service. Today, operating in more than 220 countries and territories, UPS is committed to moving our world forward by delivering what matters. UPS and its more than 500,000 UPSers around the globe are a transportation and logistics leader, offering innovative solutions to customers, big and small. UPS understands and appreciates its responsibility to help build safe, stronger and more resilient communities founded on justice and economic opportunity for all, supported by a healthy, sustainable global environment.