Principal Architect - Machine Learning

• The Principal Architect
• Machine Learning at United Airlines will lead the design, architecture, and deployment of advanced machine learning and generative AI platforms. Responsibilities include building cloud-native infrastructure, developing ML automation tools, and optimising large-scale model pipelines. The role requires a bachelor’s degree in a relevant field, at least 5 years’ experience in software engineering and machine learning, and expertise in Python, Go, Java, or C/C++. Candidates must have experience with data science frameworks, cloud-native DevOps, and generative AI/LLM operations. Legal authorisation to work in the US is required. Preferred qualifications include a master’s or PhD, experience with AWS, Kubernetes, Spark, Flink, and enterprise architecture. The base salary ranges from $147,060 to $191,516, with eligibility for bonuses and comprehensive benefits. The Principal Architect – Machine Learning at United Airlines plays a pivotal role in designing, architecting, and leading key components of the Machine Learning Platform, Gen AI/ML business use cases, and establishing best practices. This position is responsible for building high-performance, cloud-native machine learning infrastructure, enabling rapid innovation across the organisation. The role involves hands-on development of ML automation tools, data pipeline development, and optimisation of generative AI/LLM models. Compensation for this role ranges from $147,060 to $191,516 per year, with eligibility for bonus and long-term incentive awards. Comprehensive benefits include medical, dental, vision, life, accident & disability, parental leave, employee assistance programme, commuter, paid holidays, paid time off, 401(k), and flight privileges. 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.

• Build high-performance, cloud-native machine learning infrastructure and services to enable rapid innovation across United

• Set up containers and Serverless platform with cloud infrastructure

• You will design and develop tools and apps to enable ML automation using AWS ecosystem

• Build data pipelines to enable ML models for batch and real-time data

• Hands on development expertise of Spark and Flink for both real time and batch applications

• Support large scale model training and serving pipelines in distributed and scalable environment

• Stay aligned with the latest developments in cloud-native and ML ops/engineering and to experiment with and learn new technologies – Num Py, data science packages like sci-kit, microservices architecture

• Optimize, fine-tune generative AI/LLM models to improve performance and accuracy and deploy them

• Evaluate the performance of LLM models, Implement LLMOps processes to manage the end-to-end lifecycle of large language models

• Develop, optimize, fine-tune Generative AI/LLM models to improve performance and accuracy and deploy them

Qualifications

What’s needed to succeed (Minimum Qualifications):

• Bachelor's degree in

Computer Science, Data Science, Generative AI, Engineering or related discipline or Mathematics experience required

• 5+ years of software engineering experience with languages such as Python, Go, Java, or C/C++
• 5+ years of experience in machine learning, deep learning, and natural language processing
• Strong software engineering experience with Python and at least one additional language such as Go, Java, or C/C++
• Strong technical leadership and familiarity with data science methodologies and frameworks (e.g., Py Torch, Tensorflow) and preferably building and deploying production ML pipelines
• Experience in ML model life cycle development experience and prefer experience to common algorithms like XGBoost, Cat Boost, Deep Learning, etc
• Experience setting up and optimizing data stores (RDBMS/NoSQL) for production use in the ML app context
• Cloud-native DevOps, CI/CD experience using tools such as Jenkins or AWS Code Pipeline; preferably experience with Git Ops using tools such as ArgoCD, Flux, or Jenkins X
• Experience with generative models such as GANs, VAEs, and autoregressive models
• Prompt engineering: Ability to design and craft prompts that evoke desired responses from LLMs
• LLM evaluation: Ability to evaluate the performance of LLMs on a variety of tasks, including accuracy, fluency, creativity, and diversity
• LLM debugging: Ability to identify and fix errors in LLMs, such as bias, factual errors, and logical inconsistencies
• LLM deployment: Ability to deploy LLMs in production environments and ensure that they are reliable and secure
• Experience with LLMOps (Large Language Model Operations) or Agentic Ops (Agentic Operations) to manage the end-to-end lifecycle of large language models
• Experience with generative ai methods such as retrieval augmented generation (RAG) and instruction fine tuning
• 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):

• Master's/PhD degree in

Computer Science or related STEM field

• 5 + years of experience working in cloud environments (AWS preferred) - Kubernetes, Dockers, ECS and EKS
• 5 + years of experience with Big Data technologies such as Spark, Flink and SQL programming
• 5 + years of experience with cloud-native DevOps, CI/CD
• 3 – 5 + years of relevant enterprise Architecture experience
• 1+ years of experience with Generative AI/LLMs

The base pay range for this role is $147,060.00 to $191,516.00.
The base salary range/hourly rate listed is dependent on job-related, factors such as experience, education, and skills. This position is also eligible for bonus and/or long-term incentive compensation awards.

You may be eligible for the following competitive benefits: medical, dental, vision, life, accident & disability, parental leave, employee assistance program, commuter, paid holidays, paid time off, 401(k) and flight privileges.

United Airlines is an Equal Opportunity Employer. We recruit, employ, train, compensate, and promote without regard to race, color, religion, national origin, gender identity, sexual orientation, disability, age, veteran status, or any other protected category under applicable law. We provide reasonable accommodations for applicants and employees with disabilities. To request an accommodation, contact [Job Accommodations@united.com](mailto:Job Accommodations@united.com)

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.

• Build high-performance, cloud-native machine learning infrastructure and services to enable rapid innovation across United

• Set up containers and Serverless platform with cloud infrastructure

• You will design and develop tools and apps to enable ML automation using AWS ecosystem

• Build data pipelines to enable ML models for batch and real-time data

• Hands on development expertise of Spark and Flink for both real time and batch applications

• Support large scale model training and serving pipelines in distributed and scalable environment

• Stay aligned with the latest developments in cloud-native and ML ops/engineering and to experiment with and learn new technologies – Num Py, data science packages like sci-kit, microservices architecture

• Optimize, fine-tune generative AI/LLM models to improve performance and accuracy and deploy them

• Evaluate the performance of LLM models, Implement LLMOps processes to manage the end-to-end lifecycle of large language models

• Develop, optimize, fine-tune Generative AI/LLM models to improve performance and accuracy and deploy them

What’s needed to succeed (Minimum Qualifications):

• Bachelor's degree in

Computer Science, Data Science, Generative AI, Engineering or related discipline or Mathematics experience required

• 5+ years of software engineering experience with languages such as Python, Go, Java, or C/C++
• 5+ years of experience in machine learning, deep learning, and natural language processing
• Strong software engineering experience with Python and at least one additional language such as Go, Java, or C/C++
• Strong technical leadership and familiarity with data science methodologies and frameworks (e.g., Py Torch, Tensorflow) and preferably building and deploying production ML pipelines
• Experience in ML model life cycle development experience and prefer experience to common algorithms like XGBoost, Cat Boost, Deep Learning, etc
• Experience setting up and optimizing data stores (RDBMS/NoSQL) for production use in the ML app context
• Cloud-native DevOps, CI/CD experience using tools such as Jenkins or AWS Code Pipeline; preferably experience with Git Ops using tools such as ArgoCD, Flux, or Jenkins X
• Experience with generative models such as GANs, VAEs, and autoregressive models
• Prompt engineering: Ability to design and craft prompts that evoke desired responses from LLMs
• LLM evaluation: Ability to evaluate the performance of LLMs on a variety of tasks, including accuracy, fluency, creativity, and diversity
• LLM debugging: Ability to identify and fix errors in LLMs, such as bias, factual errors, and logical inconsistencies
• LLM deployment: Ability to deploy LLMs in production environments and ensure that they are reliable and secure
• Experience with LLMOps (Large Language Model Operations) or Agentic Ops (Agentic Operations) to manage the end-to-end lifecycle of large language models
• Experience with generative ai methods such as retrieval augmented generation (RAG) and instruction fine tuning
• 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):

• Master's/PhD degree in

Computer Science or related STEM field

• 5 + years of experience working in cloud environments (AWS preferred) - Kubernetes, Dockers, ECS and EKS
• 5 + years of experience with Big Data technologies such as Spark, Flink and SQL programming
• 5 + years of experience with cloud-native DevOps, CI/CD
• 3 – 5 + years of relevant enterprise Architecture experience
• 1+ years of experience with Generative AI/LLMs

Equal Opportunity Employer
The University of Missouri System is an Equal Opportunity Employer. Equal Opportunity is and shall be provided for all employees and applicants for employment on the basis of their demonstrated ability and competence without unlawful discrimination on the basis of their race, color, national origin, ancestry, religion, sex, pregnancy, sexual orientation, gender identity, gender expression, age, disability, or protected veteran status, or any other status protected by applicable state or federal law. This policy applies to all employment decisions including, but not limited to, recruiting, hiring, training, promotions, pay practices, benefits, disciplinary actions and terminations. For more information, visit https://www.umsystem.edu/ums/hr/eeo.

• All qualified applicants will receive consideration for employment without regard to race, color, national origin, ancestry, religion, sex, pregnancy, sexual orientation, gender identity, gender expression, age, disability, or protected veteran status, or any other status protected by applicable state or federal law. 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 Responsibilities
• Responsible for designing, architecting, implementing, and leading key components of the Machine Learning Platform and Gen AI/ML business use cases.
• Play a key role in shaping high-performance, cloud-native machine learning infrastructure and services to enable rapid innovation across United.
• Take ownership of setting up containers and Serverless platforms with cloud infrastructure.
• Deliver high-quality tools and applications to enable ML automation using the AWS ecosystem.
• Build data pipelines to enable ML models for both batch and real-time data processing.
• Lead efforts to support large-scale model training and serving pipelines in distributed and scalable environments.
• Help drive innovation in optimising, fine-tuning, and deploying generative AI/LLM models to improve performance and accuracy.
• Collaborate cross-functionally to evaluate the performance of LLM models and implement LLMOps processes for managing the end-to-end lifecycle of large language models.
• Support prompt engineering and LLMOps processes to design and craft prompts, evaluate, and deploy LLMs in production environments. Skills
• Demonstrated expertise in software engineering with languages such as Python, Go, Java, or C/C++.
• Strong technical leadership and familiarity with data science methodologies and frameworks, including Py Torch and Tensor Flow.
• Experience in machine learning, deep learning, and natural language processing, with preference for algorithms such as XGBoost, Cat Boost, and Deep Learning.
• Proficiency in setting up and optimising data stores (RDBMS/NoSQL) for production use in the ML app context.
• Hands-on experience with cloud-native DevOps and CI/CD tools, preferably AWS Code Pipeline, Jenkins, ArgoCD, Flux, or Jenkins X.
• Experience with generative AI/LLMs, including prompt engineering, LLMOps, retrieval augmented generation, and instruction fine-tuning.
• Experience with Spark and Flink for both real-time and batch applications.
• Experience with cloud environments, preferably AWS, and Big Data technologies such as Spark, Flink, and SQL programming.
• Experience with enterprise architecture and cloud-native DevOps, CI/CD, and LLMOps processes. Education
• A Bachelor's degree in Computer Science, Data Science, Generative AI, Engineering, Mathematics, or a related discipline is required.
• A Master's or PhD in a Computer Science or related STEM field is preferred.