AI Engineer I

Hybrid AI Engineering role with FedEx Dataworks focused on delivering production-ready AI/ML solutions across the enterprise. You will design, build, deploy, and maintain intelligent automation, predictive insight, and advanced analytics systems, with emphasis on end-to-end machine learning lifecycle execution and operational readiness.

Location: Orlando, FL (hybrid). Employees will work at the FedEx campus location several times per week, and candidates must live within 50 miles of the campus location.

Compensation: USD 7,488 - 10,444 per monthly.

Responsibilities

• Design, develop, and maintain scalable ML pipelines for training, validation, inference, and deployment.
• Collaborate with ML Ops Engineers to package and deploy models into enterprise systems using established MLOps practices.
• Monitor deployed models for performance, data drift, and reliability, and troubleshoot to resolve issues.
• Define and implement Service Level Objectives (SLOs) for key metrics such as p50/p95 latency and availability, and establish robust monitoring and alerting for drift, latency, and error rates.
• Write clean, efficient, well-documented code to develop and implement AI/ML models that support business use cases.
• Implement data engineering and preprocessing workflows required for model inputs.
• Continuously optimize performance and scalability of AI applications and models.
• Work closely with Data Scientists to transition experimental models and research prototypes into production-ready systems.
• Support integration of AI capabilities into enterprise workflows, applications, and digital platforms.
• Contribute to documentation and explainability of model outputs for business stakeholders.
• Ensure deployed AI systems comply with enterprise governance, fairness, and security standards.
• Evaluate emerging AI technologies such as LLMs and generative AI to assess applicability and drive innovation.
• Implement robust observability, including SLOs, clear incident response, and rollback strategies for AI services.

Requirements

• 5+ years of experience.
• Bachelor’s degree/Equivalent in computer science, information systems and/or equivalent formal training.
• Strong coding skills in Python, Java, or C++, including API development and software design.
• Deep understanding of core machine learning concepts including classification, regression, clustering, and deep learning architectures.
• Hands-on experience with modern deep learning frameworks and algorithms (supervised/unsupervised), such as PyTorch or TensorFlow.
• Skills working with LLMs, including prompt engineering, fine-tuning, and frameworks such as LangChain and LangGraph for RAG (Retrieval-Augmented Generation) systems.
• Experience with data wrangling, SQL, data warehousing, and ETL pipelines to prepare model inputs.
• Proven end-to-end lifecycle experience: developing, training, and deploying ML models from prototype to production.
• Mastery of data preprocessing, feature engineering, and model evaluation techniques.
• Strong ability to build and optimize scalable data pipelines for training and evaluation.
• Knowledge of SQL and NoSQL databases for querying and managing data for AI applications.
• Software engineering best practices including Git, automated testing, and CI/CD pipelines.
• Hands-on containerization with Docker and orchestration with Kubernetes.
• MLOps observability experience: model monitoring for performance and drift, plus model/version lineage, telemetry, and traceability.
• Experience with advanced testing and deployment strategies including canary/shadow deployments and test suites (unit, integration, adversarial, regression).
• Ability to integrate AI models and services into enterprise applications using RESTful APIs.
• Proficiency with at least one major cloud platform (GCP, AWS, or Azure) and associated AI/ML services (e.g., Vertex AI, SageMaker, Azure ML).
• Experience with big data technologies such as Apache Spark for large-scale dataset processing in the cloud.
• Strong problem-solving and analytical skills, including collaboration in an Agile environment.
• Excellent communication skills to explain technical concepts to technical and non-technical stakeholders.
• Experience with modern frontend JavaScript frameworks such as React, Vue.js, or Angular (for user-facing applications that consume AI models).
• Skills in IT security and infrastructure, and experience with security and risk frameworks, standards, and best practices.
• Strong technical and consulting skills, plus project management capability.
• Strong communication skill.

Technology Focus

Python, Java, C++, PyTorch, TensorFlow, LangChain, LangGraph, RAG (Retrieval-Augmented Generation), SQL, Docker, Kubernetes, Git, CI/CD, RESTful APIs, GCP, AWS, Azure, Vertex AI, SageMaker, Azure ML, Apache Spark, React, Vue.js, Angular, NoSQL