Senior Engineer, Machine Learning - Remote
North Carolina, USA
Listed on 2025-12-30
-
IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Engineer
Senior Engineer, Machine Learning - Remote
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Logistics at full potential. At GXO, we’re constantly looking for talented individuals at all levels who can deliver the caliber of service our company requires. You know that a positive work environment creates happy employees, which boosts productivity and dedication. On our team, you’ll have the support to excel at work and the resources to build a career you can be proud of.
NOTE:
This role is for the Eastern Time Zone location.
- Deploy and monitor ML models in production – Use tools like Docker, Kubernetes, and MLflow to ensure scalable and reliable deployment
- Build and maintain data pipelines – Use tools like Airflow, Spark, or Kafka to support model training and inference
- Integrate ML models into business applications – Collaborate with software engineers to embed models into operational systems
- Monitor model performance and data drift – Implement alerting and retraining pipelines
- Clean and preprocess data – Ensure data quality and consistency for modeling
- Work with cross‑functional teams – Translate business needs into technical solutions
- Maintain technical documentation – Ensure reproducibility and knowledge sharing
- Optimize ML workflows – Identify and implement improvements in performance and scalability
We are eager to attract the best, so we offer competitive compensation and a generous benefits package, including full health insurance (medical, dental and vision), 401(k), life insurance, disability and more.
What you need to succeed at GXO At a minimum, you’ll need:- Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, Economics, Physics or another analytics‑related field, or equivalent related work or military experience
- 3–5 years in AI/ML engineering or Data Science, or software engineering with ML focus
- ML Engineering Expertise:
Strong understanding of ML lifecycle, from training to deployment and monitoring. - Programming Proficiency:
Advanced Python skills; experience with ML libraries (e.g., Scikit‑learn, Tensor Flow, PyTorch). - MLOps Tools:
Proficiency in Docker, Kubernetes, MLflow, and CI/CD pipelines. - Data Engineering:
Experience with data pipeline tools (Airflow, Spark, Kafka). - Cloud Platforms:
Familiarity with AWS, GCP, or Azure.
- Collaboration:
Ability to work with data scientists, developers, and business stakeholders. - Communication:
Ability to explain GenAI concepts to technical and non‑technical stakeholders.
Mid‑Senior level
Employment typeFull‑time
Job functionEngineering and Information Technology
IndustriesTransportation, Logistics, Supply Chain and Storage
We engineer faster, smarter, leaner supply chains. GXO is a leading provider of cutting‑edge supply chain solutions to the most successful companies in the world. We help our customers manage their goods most efficiently using our technology and services. Our greatest strength is our global team – energetic, innovative people of all experience levels and talents who make GXO a great place to work.
We are proud to be an Equal Opportunity/Affirmative Action employer. Qualified applicants will receive consideration for employment without regard to race, sex, disability, veteran or other protected status.
GXO adheres to CDC, OSHA and state and local requirements regarding COVID safety. All employees and visitors are expected to comply with GXO policies which are in place to safeguard our employees and customers.
All applicants who receive a conditional offer of employment may be required to take and pass a pre‑employment drug test.
The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. All employees may be required to perform duties outside of their normal responsibilities from time to time, as needed.
Review GXO’s candidate privacy statement here.
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