About the role
Machine Learning Engineering Manager
Location Chicago, Illinois, United States This job is associated with 2 categories See allJob IdWHQ00026545Information TechnologyJob TypeFull-TimePosted Date 08/05/2026
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Description
Job overview and responsibilities
Develops and programs integrated software algorithms to structure, analyze and leverage data in systems applications. Develops and communicates statistical modeling techniques to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy. Completes programming and implements efficiencies, performs testing and debugging. Completes documentation and procedures for installation and maintenance. Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations.
Can work with large scale computing frameworks, data analysis systems and modeling environments.
Design and implement key components of the Machine Learning Platform infrastructure and establish processes and best practices
Work cross-functionally with data scientists, data engineers, and IT teams to design, develop, deploy, and integrate high-performance, production-grade machine learning solutions and data intensive workflows
Partner with data scientists and data engineers to create and refine features from underlying data and build reproducible feature pipelines to train models and serve features in production
Partner with data platform and operations teams to solve complex data ingestion, pipeline and governance problems for machine learning solutions
Take ownership of production systems with a focus on delivery, continuous integration, and automation of machine learning workloads
Provide technical mentorship, guidance, and quality-focused code review to data scientists and ML engineers
Qualifications
What’s needed to succeed (Minimum Qualifications):
Bachelor’s degree in computer science, engineering, or a related technical discipline
3+ years of experience in managing technical teams and projects
3+ years of experience in full software lifecycle development using Python
3+ years of experience leading an ML Ops team familiar with large cloud environments, Big Data technologies
3+ years in software development in Python, Java, PySpark
3+ Years of Experience with Machine Learning and Machine Learning workflows
3+ years of experience designing and developing using technologies as Docker, Kubernetes
Strong software engineering experience with Python and at least one additional language such as Java, Go, Rust, or C/C++
Understanding of machine learning principles and techniques
Experience with data science tools and frameworks (e.g. PyTorch, Tensorflow, Keras, Pandas, Numpy, Spark)
Experience designing and developing scalable cloud native solutions using technologies such as Docker and Kubernetes and serverless services such as AWS Lambda, EKS, ECS, Fargate
Experience building infrastructure-as-code templates (e.g. AWS CloudFormation) and cloud-native CI/CD pipelines using tools such as AWS CodePipeline
Experience building ETL pipelines and working with big data technologies (e.g. Hadoop, Spark, and serverless technologies such as EMR, Redshift, S3, AWS Glue, and Kinesis)
Knowledge of distributed systems as it pertains to compute and data storage
Strong desire to experiment with and learn new technologies and stay aligned with the latest community developments in ML Ops/Engineering and cloud native
Excellent oral and written communication skills. Ability to prepare high-quality presentation materials and explain complex concepts and technical materials to less-technical audiences
Must be legally authorized to work in the United States for any employer without sponsorship
Successful completion of interview required to meet job qualification
Reliable, punctual attendance is an essential function of the position
What will help you propel from the pack (Preferred Qualifications):
AWS Certified Solution Architect (Associate or Professional)
Experience working as a Machine Learning Engineer or Data Scientist building and productional machine learning solutions
Experience building real-time event-driven stream processing solutions with technologies such as Kafka, Flink, and Spark
Experience with GPU acceleration (e.g. CUDA and CuDNN)
Experience with Kubernetes
The base pay range for this role is $117,610.00 to $153,146.00.
Minimum requirements
- Bachelor’s degree in computer science, engineering, or related field with 3+ years managing technical teams and projects
- 3+ years in full software lifecycle development using Python, Java, PySpark, and leading ML Ops in large cloud/Big Data environments
- Experience with machine learning workflows, Docker, Kubernetes, cloud-native solutions, and strong software engineering skills in Python plus another language
This listing was parsed by AI and may not be complete. Check the official posting on United Airlines's site for the most accurate information.