Senior Manager - Machine Learning Engineering

There’s never been a more exciting time to join United Airlines! We’re on a path towards becoming the best airline in the history of aviation. And we’re growing – in the years ahead, we’ll hire tens of thousands of people across every area of the airline. Our careers include competitive benefits package aimed at keeping you happy, healthy, and well-traveled. From employee-run "Business Resource Group" communities to world-class benefits like parental leave, 401k, and privileges like space available travel, United is truly a one-of-a-kind place to work. Are you ready to travel the world?

We believe that inclusion propels innovation and is the foundation of all that we do. United&39;s Digital Technology team spans the globe and is made up of diverse individuals all working together with pioneering technology to make United the best airline in the history of aviation.

The Senior Manager, ML Engineering & Data Operations will be a critical part of the team responsible for enterprise-wide ML Engineering and Platform environment. This role requires a high level of technical expertise in building enterprise-wide big data infrastructure and be the expert in all phases of data & software lifecycle management processes.

The Senior Manager will lead, mentor, and guide the team of ML Engineers with highest standards for quality, maintainability, and performance. This role will ensure ML Ops best practices are followed and build the ML Platform to deploy and monitor ML models for the enterprise. Additionally, this individual will collaborate with DataOps and Data Engineering teams to set the strategic direction prioritize goals.

This is a highly visible role with excellent exposure and opportunity to make immediate impact on ML practices. This strong leader will showcase & continually develop ML/AI skills in enterprise cloud and data platforms (AWS), Palantir Foundry.

Candidates local/commutable to Chicago or Houston areas (or willing to relocate) will be considered first/as priority. This is a hybrid role a to be onsite as needed/ on occasion.

Responsibilities

• Design, Manage, and Monitor, ML Engineering platform to support enterprise needs
• Design and implement Feature Engineering/data engineering pipelines and develop solutions including applications to deliver inferencing outcomes or curated data layer/datasets for consuming applications
• Develop systems, tools & processes to monitor ML models in production, monitoring drift and performance and initiating retraining and validation as necessary
• Establish scalable, efficient, and automated processes for large scale ML model deployments
• Develop solutions on Analytics platform (like Palantir Foundry) and work closely with Data Science,Data Engineering and DataOps teams to deploy ML apps and other integrations
• Develop systems, tools, & processes to govern ML models for compliance, bias, versioning, traceability, and auditability
• Recommend and drive architecture/infrastructure to create concrete, meaningful, and scalable solutions for business problems

• Bachelor&39;s Degree (or higher) in Computer Science, Data Science, Engineering or related subject area or Mathematics experience required
• 10+ years in managing technical teams and projects
• 4+ years leading an ML Ops team familiar with large cloud environments, Data technologies
• 4 + years in software development in Python, C++ and infrastructure development
• 4+ Years in Machine Learning and Machine Learning workflows
• Knowledge of common machine learning frameworks–Torch, Tensorflow,Sci-kit
• Knowledge of major cloud computing services – AWS
• Experience with on-prem distributed computing services – OpenShift, Hadoop
• Knowledge of devOps – Continuous Integration, Continuous Deployment
• Experience with HPC – CUDA
• Experience building auto-scaling ML systems
• Experience in Distributed computing, Data pipelines, and AI/ML
• Experience setting up and optimizing databases for production usage for ML app context as feature store and model monitoring
• Experience in Kubernetes, Jenkins, GITOps
• Experience in Spark, Kafka, HDFS, Cassandra
• Strong Python, Scripting Experience, Jupyter notebooks
• Experience with Feature engineering, text classification, and time series prediction and other ML frameworks
• Experience in Data Science Model Deployment & Support/ Maintenance
• Experience with database systems including Redshift, MS SQL Server,Oracle, Tearadata, BigQuery, Postgres
• Must be legally authorized to work in the United States for any employer without sponsorship
• AWS Certified Machine Learning preferred

United Airlines is an equal opportunity employer. United Airlines recruits, employs, trains, compensates and promotes regardless of race, religion, color, national origin, gender identity, sexual orientation, physical ability, age, veteran status, and other protected status as required by applicable law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions. Please contact JobAccommodationsunited.com to request accommodation.