ML Platform Leader: Cloud-Native ML & LLM Ops

We believe that inclusion propels innovation and is the foundation of all that we do. United's Digital Technology team spans the globe and is made up of diverse 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. Key Responsibilities: United Airlines is seeking dedicated professionals 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 data scientists and data engineers. The person in this role will design and implement key components of the Machine Learning Platform, 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 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 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 – NumPy, 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 United values diverse experiences, perspectives, and we encourage everyone who meets the minimum qualifications to apply. While having the “desired” qualifications make for a stronger candidate, we encourage applicants who may not feel they check ALL of those boxes! We are always looking for individuals who will bring something new to the table! Qualifications What’s needed to succeed (Minimum Qualifications): Bachelor’s Degree in Computer Science, Engineering, or a related technical field 8+ years of software engineering experience with languages such as Python, Go, Java, Scala, Kotlin, or C/C++ 6+ years of experience in machine learning, deep learning, and natural language processing 4 + years of experience working in cloud environments (AWS preferred) - Kubernetes, Dockers, ECS and EKS 2 + years of experience with Big Data technologies such as Spark, Flink and SQLprogramming 3 + years of experience with cloud-native DevOps, CI/CD 1+ years of experience with Generative AI/LLMs Familiarity with data science methodologies and frameworks (e.g., PyTorch, 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, CatBoost, Deep Learning, etc Cloud-native DevOps, CI/CD experience using tools such as Jenkins or AWS CodePipeline; preferably experience with GitOps using tools such as ArgoCD, Flux, or Jenkins X Experience writing, testing, and deploying one or more ML solutions using one or more of the following declarative infrastructure as code solutions: Terraform, Pulumi, AWS CloudFormation, Azure Resource Manager, or GCP Deployment Manager Experience with generative models such as GANs, VAEs, and autoregressive models Experience with LLMOps (Large Language Model Operations) to manage the end-to-end lifecycle of large language models Prompt engineering: Ability to design and craft prompts that evoke desired responses from LLMs Must be legally authorized to work in the United States for any employer without sponsorship What will help you propel from the pack (Preferred Qualifications): Master's/PhD degree #J-18808-Ljbffr United Airlines, Inc.