Machine Learning Engineering Manager

United Airlines - Houston, TX

Full-time - Senior

Houston, TX

Air Transportation

About the position

The Machine Learning Engineering Manager at United Airlines is responsible for leading the Data and Machine Learning Engineering team, focusing on data-driven insights and innovations to support machine learning needs for commercial and operational projects. This role involves collaboration with data scientists and engineers to design and implement key components of the Machine Learning Platform, establish best practices, and build high-performance, cloud-native machine learning infrastructure. The position emphasizes rapid innovation, model training, and deployment in a scalable environment, while staying aligned with the latest developments in machine learning and cloud technologies.

Responsibilities

• Lead the Data and Machine Learning Engineering team to support machine learning needs for commercial and operational projects.
• Collaborate with data scientists and data engineers to design and implement key components of the Machine Learning Platform.
• Establish processes and best practices for machine learning operations.
• Build high-performance, cloud-native machine learning infrastructure and services.
• 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 developments in cloud-native and ML ops/engineering and experiment with new technologies.
• 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.
• 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, and Deep Learning.
• Experience with CI/CD tools such as Jenkins or AWS CodePipeline.

Nice-to-haves

• Master's or PhD degree in a related field.

Benefits

• 401(k)
• Parental leave
• Space available travel privileges