GXO Logistics, Inc. is a leading provider of cutting-edge supply chain solutions. As a Machine Learning Engineer, you will design, build, and maintain scalable machine learning systems while collaborating with data scientists and software engineers to optimize performance across 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
- Work closely with IT teams (infrastructure, InfoSec, data engineering) to define internal requirements and ensure seamless integration
- Communicate effectively with leadership to secure resources, address issues, and provide project updates
- Take ownership of projects end-to-end with minimal supervision
- 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, and 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
- 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