Architect
US$147,000 – US$191,500 / yr base salary
Posted 7 Oct 2026
Advertised as “Principal Architect - Machine Learning”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5+ yrs
- Management level
- Individual contributor
- Visa sponsorship
- Not offered
| Base salary | US$147,000 – US$191,500 / yr |
|---|
Field of studyComputer Science, Data Science, Engineering, Generative AI, Mathematics (or related)
Study levelBachelor's
Field of studyComputer Science, STEM (or related)
Study levelMaster's or higher
Achieving our goals starts with supporting yours. Grow your career, access top-tier health and wellness benefits, build lasting connections with your team and our customers, and travel the world using our extensive route network.
Come join us to create what’s next. Let’s define tomorrow, together.
Description
United's Digital Technology team is comprised of many talented individuals all working together with cutting-edge technology to build the best airline in the history of aviation. Our team designs, develops and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, and digital solutions.
Job overview and responsibilities
United Airlines is seeking talented people to join the Data and Machine Learning Engineering team. The organization is responsible for leading data driven insights & innovation to support the Machine Learning needs for commercial and operational projects with a digital focus. This role will frequently collaborate with ML engineers, data scientists and data engineers. This role will design, architect, implement and lead key components of the Machine Learning Platform, Gen AI/ML business use cases, and establish processes and best practices.
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Build high-performance, cloud-native machine learning infrastructure and services to enable rapid innovation across United
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Set up containers and Serverless platform with cloud infrastructure
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You will design and develop tools and apps to enable ML automation using AWS ecosystem
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Build data pipelines to enable ML models for batch and real-time data
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Hands on development expertise of Spark and Flink for both real time and batch applications
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Support large scale model training and serving pipelines in distributed and scalable environment
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Stay aligned with the latest developments in cloud-native and ML ops/engineering and to experiment with and learn new technologies – NumPy, data science packages like sci-kit, microservices architecture
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Optimize, fine-tune generative AI/LLM models to improve performance and accuracy and deploy them
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Evaluate the performance of LLM models, Implement LLMOps processes to manage the end-to-end lifecycle of large language models
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Develop, optimize, fine-tune Generative AI/LLM models to improve performance and accuracy and deploy them