Principal Architect - Data Science

United Airlines - Chicago, IL

Full-time - Mid Level

Chicago, IL

Air Transportation

About the position

United Airlines is seeking a talented individual to join the Data and Machine Learning Engineering team, responsible for leading data-driven insights and innovation to support Machine Learning needs for commercial and operational projects. This role involves designing, architecting, implementing, and leading key components of the Machine Learning Platform, focusing on generative AI and ML business use cases, while establishing processes and best practices.

Responsibilities

• Collaborate with ML engineers, data scientists, and data engineers to support machine learning initiatives.
• Design, architect, and implement key components of the Machine Learning Platform.
• Build high-performance, cloud-native machine learning infrastructure and services.
• Set up containers and serverless platforms with cloud infrastructure.
• Design and develop tools and applications for ML automation using the AWS ecosystem.
• Build data pipelines for batch and real-time data to enable ML models.
• Support large-scale model training and serving pipelines in a distributed environment.
• Stay updated with the latest developments in cloud-native and ML ops/engineering.
• Optimize and fine-tune generative AI/LLM models for performance and accuracy.
• Evaluate the performance of LLM models and implement LLMOps processes.

Requirements

• Bachelor's degree in Computer Science, Data Science, Generative AI, Engineering, Mathematics, or a related discipline.
• 7+ years of software engineering experience with languages such as Python, Go, Java, Scala, Kotlin, or C/C++.
• 7+ years of experience in machine learning, deep learning, and natural language processing.
• Strong technical leadership and familiarity with data science methodologies and frameworks (e.g., PyTorch, Tensorflow).
• Experience in ML model lifecycle development and familiarity with algorithms like XGBoost, CatBoost, and Deep Learning.
• Experience setting up and optimizing data stores (RDBMS/NoSQL) for production use in ML applications.
• Cloud-native DevOps, CI/CD experience using tools such as Jenkins or AWS CodePipeline.
• Experience with generative models such as GANs, VAEs, and autoregressive models.
• Ability to design and craft prompts for LLMs, evaluate their performance, debug errors, and deploy them in production.

Nice-to-haves

• Master's/PhD degree in Computer Science or related STEM field.
• 5+ years of experience working in cloud environments (AWS preferred) including Kubernetes, Dockers, ECS, and EKS.
• 5+ years of experience with Big Data technologies such as Spark, Flink, and SQL programming.
• 5+ years of experience with cloud-native DevOps and CI/CD.
• 3-5+ years of relevant enterprise architecture experience.

Benefits

• Competitive benefits package including parental leave, 401k, and travel privileges.