Machine Learning Engineering Manager

United Airlines - Chicago, IL

Full-time - Mid Level

Chicago, IL

5,001-10,000 employees

Air Transportation

About the position

United Airlines is seeking experienced professionals to join its Data and Machine Learning Engineering team, which is responsible for driving data-driven insights and innovations to support machine learning initiatives for commercial and operational projects. The role involves designing and implementing key components of the Machine Learning Platform, collaborating with data scientists and engineers, and building high-performance, cloud-native machine learning infrastructure to enable rapid innovation across the airline.

Responsibilities

• Collaborate with data scientists and data engineers to support machine learning needs.
• Design and implement key components of the Machine Learning Platform and business use cases.
• Establish processes and best practices for machine learning operations.
• Build high-performance, cloud-native machine learning infrastructure and services.
• Develop tools and applications for ML automation using the AWS ecosystem.
• Create data pipelines for batch and real-time data to support 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, Engineering, or a related technical field.
• 8+ years of software engineering experience with languages such as Python, Go, Java, Scala, Kotlin, or C/C++.
• 6+ years of experience in machine learning, deep learning, and natural language processing.
• 4+ years of experience working in cloud environments (AWS preferred) including Kubernetes, Dockers, ECS, and EKS.
• 2+ years of experience with Big Data technologies such as Spark, Flink, and SQL programming.
• 3+ years of experience with cloud-native DevOps and CI/CD processes.
• 1+ years of experience with Generative AI/LLMs.
• Familiarity with data science methodologies and frameworks (e.g., PyTorch, Tensorflow).
• Experience in ML model lifecycle development and common algorithms like XGBoost, CatBoost, Deep Learning, etc.
• Experience with cloud-native DevOps using tools such as Jenkins or AWS CodePipeline.

Nice-to-haves

• Master's/PhD degree in a relevant field.

Benefits

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