AI/ML Engineer

About the job

The Pricing Data Science team within Revenue Management at FedEx develops advanced analytics, machine learning models, and intelligent applications that power pricing strategy, revenue optimization, and decision support across the enterprise. Our work directly influences margin performance, customer segmentation, contract pricing, and strategic initiatives. Role Overview: We are seeking a highly skilled AI/ML Engineer who can build, deploy, and scale machine learning models and full-stack applications in modern cloud environments (Azure and/or GCP). This role requires strong end-to-end ownership — from model development to production deployment and application integration — with an emphasis on scalable, secure, and enterprise-ready systems. Key Responsibilities: - AI / Machine Learning - Design, build, and optimize machine learning models for pricing, forecasting, and revenue optimization use cases - Develop production-grade ML pipelines for training, evaluation, and inference - Implement MLOps best practices including versioning, monitoring, retraining, and governance - Collaborate with data scientists and business stakeholders to translate business problems into scalable AI solutions - Cloud & Infrastructure - Architect and deploy ML solutions in Azure and/or GCP - Build scalable cloud-native architectures leveraging services such as: Azure ML, Databricks, Synapse, AKS GCP Vertex AI, BigQuery, GKE - Implement CI/CD pipelines for model and application deployment - Ensure system reliability, security, performance, and cost optimization - Application Development - Develop and scale web-based AI applications using: React.js (preferred) or other modern front-end frameworks (Angular, Vue, etc.) - Backend frameworks such as Python (FastAPI, Flask), Node.js, or similar - Build APIs to expose ML models for internal business consumption - Integrate front-end interfaces with ML services and backend systems - Containerization & DevOps (Strong Plus) - Containerize applications and ML services using Docker - Deploy and manage workloads in Kubernetes (AKS, GKE, or similar) - Implement monitoring and observability tools for production systems Required Qualifications: - Bachelor’s or master’s degree in computer science, Data Science, Engineering, or related field - 3-6 years of experience building ML models in production environments - Strong proficiency in Python - Hands-on experience with Azure and/or GCP cloud ecosystems - Experience building scalable web applications using React.js or comparable frameworks - Experience building RESTful APIs and integrating ML services into applications - Solid understanding of software engineering best practices (testing, version control, CI/CD) Preferred Qualifications: - Experience with Docker and Kubernetes in production environments - Familiarity with MLOps frameworks (MLflow, Kubeflow, Vertex AI pipelines, etc.) - Experience with large-scale data processing (Spark, Databricks, BigQuery) - Experience in pricing, revenue management, supply chain, or logistics analytics - Experience with model monitoring, drift detection, and production support.

Requirements

• AI
• Machine Learning
• Python
• Azure
• GCP
• React.js
• RESTful APIs
• Docker
• Kubernetes

Qualifications

• Bachelor’s or master’s degree in computer science
• Data Science
• Engineering
• related field

Preferred Technologies

• AI
• Machine Learning
• Python
• Azure
• GCP
• React.js
• RESTful APIs
• Docker
• Kubernetes

About the company

FedEx provides advanced analytics, machine learning models, and intelligent applications that power pricing strategy, revenue optimization, and decision support across the enterprise.