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United Airlines Senior Manager - Machine Learning in Chicago, Illinois

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The United IT team designs, develops and maintains massively scaling technology solutions that are brought to life with innovative architectures, data analytics and digital solutions.

Job overview and responsibilities

We are looking for a Senior Manager, ML Engineering & Data Operations to join United Data Engineering team. This role would be part of a team that is responsible for enterprise-wide ML Engineering and Platform environment. In addition to requiring a high level of technical expertise in building enterprise wide big data infrastructure, you will work closely with peer business teams & Analytics team to innovate around business processes. Ideal candidates will have expertise in all phases of data & software lifecycle management processes.

This opportunity is a great fit for someone with proven leadership experience in ML Engineering and operations, and provides a venue to develop new skills in enterprise cloud and data platforms such as Amazon Web Services (AWS), Palantir Foundry and help evolve ML Practice.

As a senior manager, you will play a key role leading a team of ML Engineers who will look to you for advice on technical and business challenges. You will guide the team and insist on highest standards for quality, maintainability, and performance. You will ensure that ML Ops best practices are followed and will be responsible to build the ML Platform to deploy and monitor ML models for the enterprise. This role also includes working with DataOps and Data Engineering development team. You will set the strategic direction as well as own and prioritize goals for your team. Successful candidates will be high-bandwidth leaders who can cut through the noise, simplify relentlessly, deliver results, and build great teams around themselves.

Additional responsibilities include but are not limited to the following:

  • Design and Manage, 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 ad other intergration

  • Develop systems, tools, & processes to govern ML models for compliance, bias, versioning, traceability and auditability

  • Recommend and drive architecture/infrastructure to create actionable, meaningful, and scalable solutions for business problems


  • Bachelor's Degree (or higher) in Computer Science, Data Science, Engineering or related discipline or Mathematics experience

  • 12+ years of experience in managing technical teams and projects

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

  • 4 + years in software development in Python, C++ and infrastructure development

  • 4+ Years of Experience with 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 – CUDAExperience 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

  • Strong verbal and written communication skills, including the ability to interact effectively with colleagues of varying technical and non-technical abilities

  • 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

  • Successful completion of interview required to meet job qualifications

  • Reliable, punctual attendance is an essential function of the position


  • AWS Cerified Machine Learning


Equal Opportunity Employer – Minorities/Women/Veterans/Disabled/LGBT

Division: 47 Technology/IT

Function: Information Technology

Equal Opportunity Employer – Minorities/Women/Veterans/Disabled