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United Airlines · 1 day ago

Machine Learning Engineering Manager

Chicago, IL

Full-time

Onsite

Mid, Senior Level

$115K/yr - $149K/yr

4+ years exp

United Airlines is dedicated to creating the best airline in the history of aviation through innovative technology solutions. The Machine Learning Engineering Manager will develop and implement machine learning infrastructure, collaborate with cross-functional teams, and mentor data scientists and ML engineers to enhance product performance and efficiency.

HospitalityIn-Flight EntertainmentService IndustryTransportationTravel

No H1B

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 workflow

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

Qualification

Machine LearningPythonML OpsCloud TechnologiesDockerKubernetesBig DataData Science ToolsETL PipelinesDesire to LearnCommunication SkillsTeam ManagementPresentation Skills

Required

Bachelor's degree in computer science, Engineering, or a related technical discipline

4-8 years of experience in managing technical teams and projects

4+ years of experience in full software lifecycle development using Python

4+ years of experience leading an ML Ops team familiar with large cloud environments, Big Data technologies

4+ years in software development in Python, Java, PySpark

4+ Years of Experience with Machine Learning and Machine Learning workflows

3+ years of experience designing an 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