Senior Engineer, Machine Learning

About This Role

This role involves designing, building, and maintaining scalable machine learning systems to transform transportation logistics through technology. The Machine Learning Engineer will work with data scientists, software engineers, and stakeholders to deploy models, ensure reliability, and optimize performance across GXO’s operations.

Responsibilities

• Design, develop, deploy, and maintain ML systems, microservices, and software components that enhance and support supply chain operations and technology
• Ensure software engineering, DevOps, and cybersecurity best practices in development and deployment, including CI/CD pipelines, source control, and secure coding standards
• Design and build, and/or collaborate with data engineering teams to develop data models, pipelines, and integration layers that support and feed ML solutions, ensuring scalability, reliability, and data quality
• Develop ML integration APIs and services using Python, SQL, and frameworks such as Flask and FastAPI with a focus on reliability, latency, and maintainability
• Build agile and portable ML solutions using containerization tools like Docker and Kubernetes
• Implement monitoring, alerting, and observability for ML services
• Collaborate with business and product stakeholders to understand use cases and educate teams on ML capabilities
• Mentor junior engineers on best practices in ML and software development through pair programming, code reviews, and architectural guidance
• Stay current on emerging ML and platform technologies and contribute to the organization’s ML roadmap
• Maintain high-quality technical documentation across systems, services, pipelines, and deployment workflows

Requirements

• 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 of experience in software engineering, ML engineering, or data science, with at least 2 years focused on designing, building, and deploying scalable, production-grade machine learning systems
• Strong proficiency in cloud environments (GCP preferred; AWS and Azure acceptable)
• Expertise in Python, APIs, SQL, system design, DevOps/MLOps
• Familiarity with distributed systems
• Familiarity with common ML frameworks such as TensorFlow, scikit-learn, PyTorch, and related tooling
• Experience in monitoring, troubleshooting, and optimizing deployed solutions
• Strong analytical and problem-solving skills
• Strong understanding of all stages of the ML lifecycle

Qualifications

• 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 of experience in software engineering, ML engineering, or data science, with at least 2 years focused on designing, building, and deploying scalable, production-grade machine learning systems

Nice to Have

• Familiarity with logistics systems and supply chain systems (e.g., WMS, OMS, TMS)
• Experience with Snowflake and its ecosystem
• Hands-on experience with GCP Vertex AI
• Experience with JavaScript and integrating ML outputs in user-facing applications

Skills

* Required skills

Benefits