United Airlines
Overview
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
We’re seeking a strategic and technically strong Senior Manager, Machine Engineering to lead our enterprise ML and GenAI platform. This individual will drive architecture, development, and operations of our ML engineering and GenAI systems, enabling scalable and responsible AI solutions across the business. The ideal candidate brings a deep understanding of ML infrastructure and MLOps, combined with hands-on or architectural experience in LLMs, RAG pipelines, and GenAI application integration. You’ll lead a team of ML engineers and collaborate cross-functionally with Data Science, Data Engineering, DevOps, and business units to deliver impactful AI outcomes at scale. Strategic Leadership & Platform Ownership: Define and execute the ML/GenAI platform strategy aligned with enterprise digital transformation objectives; own the platform roadmap, architecture decisions, and budget planning to scale AI capabilities across the enterprise; collaborate with CDO, CIO, and senior stakeholders to identify, prioritize, and fund AI/GenAI investments; represent the ML Center of Excellence (COE in cross-functional meetings and strategic planning forums; serve as the primary liaison between the COE and business units, communicating technical capabilities and business impact. GenAI & LLM Strategy: Lead initiatives around LLMs and foundation models; design and operationalize GenAI pipelines (RAG, prompt orchestration, fine-tuning, safety guardrails); build and deploy secure, scalable GenAI applications with emphasis on privacy, safety, and compliance; integrate LLMs into enterprise workflows (copilots, document summarization, intelligent assistants, domain-specific Q&A). ML Engineering & MLOps: Design, manage, and monitor the enterprise ML engineering platform for scalability, reliability, and automation; own ML production systems with focus on CI/CD, observability, and resilient architecture; develop robust MLOps processes to monitor model performance, detect drift, and automate retraining and validation; build and maintain tools to govern ML models for compliance, bias, versioning, traceability, and auditability. Data Engineering & Feature Platforms: Design and implement feature engineering and data pipelines to deliver high-quality training data and inference-ready datasets; partner with data scientists and engineers to create reusable, production-grade feature stores and pipelines; solve complex data ingestion, transformation, and governance challenges with data platform and DataOps teams; develop integrated ML/AI solutions on enterprise analytics platforms (e.g., Palantir Foundry, Databricks). Team Leadership & Talent Development: Hire, mentor, and grow a high-performing ML engineering team with a focus on innovation, execution, and impact; provide technical mentorship to ML engineers and data scientists; promote a culture of continuous learning, experimentation, and operational excellence; build auto-scaling ML systems. ML Engineering & MLOps Tools & Platforms: Experience with MLflow, KServe, SageMaker, Vertex AI, Databricks, and related tooling. GenAI & Data Infra: Experience with LLM providers (OpenAI, Anthropic), Hugging Face, LangChain/LlamaIndex; data infra including Spark, Kafka, Delta Lake; DevOps capabilities including Kubernetes, Jenkins, GitOps, Terraform. Qualifications
Minimum Qualifications: Bachelor's degree in Computer Science, Data Science, Engineering or a relevant field 7+ years of relevant experience Experience leading ML Ops teams Gen AI technology experience Understanding of architecture and relevant tools like PySpark, MLflow, LangChain, AWS, or similar 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 Preferred Qualifications: 9+ years preferred Experience in platform enablement, ML pipeline creation, management, and feature engineering 5+ years of software development experience 2+ years of GenAI experience The base pay range for this role is $143,450.00 to $186,778.00 per year. 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. 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. Equal Opportunity Employer - Minorities/Women/Veterans/Disabled/LGBT. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process. Please contact JobAccommodations@united.com to request accommodation. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries Airlines and Aviation Referrals increase your chances of interviewing at United Airlines by 2x
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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
We’re seeking a strategic and technically strong Senior Manager, Machine Engineering to lead our enterprise ML and GenAI platform. This individual will drive architecture, development, and operations of our ML engineering and GenAI systems, enabling scalable and responsible AI solutions across the business. The ideal candidate brings a deep understanding of ML infrastructure and MLOps, combined with hands-on or architectural experience in LLMs, RAG pipelines, and GenAI application integration. You’ll lead a team of ML engineers and collaborate cross-functionally with Data Science, Data Engineering, DevOps, and business units to deliver impactful AI outcomes at scale. Strategic Leadership & Platform Ownership: Define and execute the ML/GenAI platform strategy aligned with enterprise digital transformation objectives; own the platform roadmap, architecture decisions, and budget planning to scale AI capabilities across the enterprise; collaborate with CDO, CIO, and senior stakeholders to identify, prioritize, and fund AI/GenAI investments; represent the ML Center of Excellence (COE in cross-functional meetings and strategic planning forums; serve as the primary liaison between the COE and business units, communicating technical capabilities and business impact. GenAI & LLM Strategy: Lead initiatives around LLMs and foundation models; design and operationalize GenAI pipelines (RAG, prompt orchestration, fine-tuning, safety guardrails); build and deploy secure, scalable GenAI applications with emphasis on privacy, safety, and compliance; integrate LLMs into enterprise workflows (copilots, document summarization, intelligent assistants, domain-specific Q&A). ML Engineering & MLOps: Design, manage, and monitor the enterprise ML engineering platform for scalability, reliability, and automation; own ML production systems with focus on CI/CD, observability, and resilient architecture; develop robust MLOps processes to monitor model performance, detect drift, and automate retraining and validation; build and maintain tools to govern ML models for compliance, bias, versioning, traceability, and auditability. Data Engineering & Feature Platforms: Design and implement feature engineering and data pipelines to deliver high-quality training data and inference-ready datasets; partner with data scientists and engineers to create reusable, production-grade feature stores and pipelines; solve complex data ingestion, transformation, and governance challenges with data platform and DataOps teams; develop integrated ML/AI solutions on enterprise analytics platforms (e.g., Palantir Foundry, Databricks). Team Leadership & Talent Development: Hire, mentor, and grow a high-performing ML engineering team with a focus on innovation, execution, and impact; provide technical mentorship to ML engineers and data scientists; promote a culture of continuous learning, experimentation, and operational excellence; build auto-scaling ML systems. ML Engineering & MLOps Tools & Platforms: Experience with MLflow, KServe, SageMaker, Vertex AI, Databricks, and related tooling. GenAI & Data Infra: Experience with LLM providers (OpenAI, Anthropic), Hugging Face, LangChain/LlamaIndex; data infra including Spark, Kafka, Delta Lake; DevOps capabilities including Kubernetes, Jenkins, GitOps, Terraform. Qualifications
Minimum Qualifications: Bachelor's degree in Computer Science, Data Science, Engineering or a relevant field 7+ years of relevant experience Experience leading ML Ops teams Gen AI technology experience Understanding of architecture and relevant tools like PySpark, MLflow, LangChain, AWS, or similar 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 Preferred Qualifications: 9+ years preferred Experience in platform enablement, ML pipeline creation, management, and feature engineering 5+ years of software development experience 2+ years of GenAI experience The base pay range for this role is $143,450.00 to $186,778.00 per year. 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. 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. Equal Opportunity Employer - Minorities/Women/Veterans/Disabled/LGBT. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process. Please contact JobAccommodations@united.com to request accommodation. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries Airlines and Aviation Referrals increase your chances of interviewing at United Airlines by 2x
#J-18808-Ljbffr