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.

• 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-end lifecycle of large language models.
• This position is offered on local terms and conditions within United’s wholly owned subsidiary United Airlines Business Services Pvt. Ltd
• Expatriate assignments and sponsorship for employment visas, even on a time-limited visa status, will not be awarded.

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

• 10 + years of software engineering experience with languages such as Python, Go, Java, Scala, Kotlin, or C/C++

• 8+ years of experience in machine learning, deep learning, and natural language processing.

• 6 + years of experience working in cloud environments (AWS preferred) – Kubernetes, Dockers, ECS and EKS.

• 6 + years of experience with Big Data technologies such as Spark, Flink and SQLprogramming.

• 6 + 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 like XGBoost, CatBoost, 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 CodePipeline; preferably experience with GitOps 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) to manage the end-to-end lifecycle of large language models.

Preferred

• Computer Science or related STEM field