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Job TitleEngineer, Machine Learning - Remote
CompanyGXO Logistics, Inc.
Job LocationNorth Carolina, United States
Workplace Type
Job Typefulltime
Job CategoryEngineering and Information Technology
Min Pay0
Max Pay0
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Last Seen 6 day(s) ago
DescriptionLogistics 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. We’re out to transform transportation logistics through technology and our multimillion-dollar commitment to IT underscores its importance to our vision. As a Machine Learning Engineer you will be responsible for designing building and maintaining scalable machine learning systems. You will work closely with data scientists software engineers and business stakeholders to deploy models into production ensure system reliability and optimize performance across GXO’s operations. Pay Benefits And More. 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’ll do on a typical day: 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 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 TensorFlow 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. It’d be great if you also had: Collaboration: Ability to work with data scientists developers and business stakeholders. Communication: Ability to explain GenAI concepts to technical and non-technical stakeholders. 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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