**Description** United's Digital Technology team designs, develops, and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, and digital solutions. Find your future at United! We’re reinventing what our industry looks like, and what an airline can be – from the planes we fly to the people who fly them. When you join us, you’re joining a global team of 100,000+ connected by a shared passion with a wide spectrum of experience and skills to lead the way forward.   Achieving our ambitions starts with supporting yours. Evolve your career and find your next opportunity. Get the care you need with industry-leading health plans and best-in-class programs to support your emotional, physical, and financial wellness. Expand your horizons with travel across the world’s biggest route network. Connect outside your team through employee-led Business Resource Groups.   Create what’s next with us. Let’s define tomorrow together. **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 data scientists and data engineers. This role will design and implement key components of the Machine Learning Platform, business use cases, and establish processes and best practices. **This position is offered on local terms and conditions. Expatriate assignments and sponsorship for employment visas, even on a time-limited visa status, will not be awarded.** 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. · 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 – 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-ed lifecycle of large language models. **Qualifications** **Required** · Bachelor's degree in compute Science, Data Science, Generative AI, Engineering or related discipline or Mathematics experience required · 6+ years of software engineering experience with languages such as Python, Go, Java, Scala, Kotlin, or C/C++. · 5+ years of experience in machine learning, deep learning, and natural language processing. · 3+ 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. · Strong software engineering experience with Python and at least one additional language such as Go, Java, or C/C+· 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 **Preferred** · Master's degree · Computer Science or related STEM field